Overview

Dataset statistics

Number of variables62
Number of observations135
Missing cells3407
Missing cells (%)40.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.5 KiB
Average record size in memory496.9 B

Variable types

Numeric13
Categorical39
Unsupported10

Alerts

airdate has constant value "2020-12-25" Constant
_embedded.show._links.nextepisode.href has constant value "https://api.tvmaze.com/episodes/2338363" Constant
_embedded.show.network.id has constant value "239.0" Constant
_embedded.show.network.name has constant value "Россия 1" Constant
_embedded.show.network.country.name has constant value "Russian Federation" Constant
_embedded.show.network.country.code has constant value "RU" Constant
_embedded.show.network.country.timezone has constant value "Asia/Kamchatka" Constant
_embedded.show.dvdCountry.name has constant value "Russian Federation" Constant
_embedded.show.dvdCountry.code has constant value "RU" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Kamchatka" Constant
url has a high cardinality: 135 distinct values High cardinality
name has a high cardinality: 121 distinct values High cardinality
_links.self.href has a high cardinality: 135 distinct values High cardinality
_embedded.show.url has a high cardinality: 80 distinct values High cardinality
_embedded.show.name has a high cardinality: 80 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 61 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 69 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 75 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 75 distinct values High cardinality
_embedded.show.summary has a high cardinality: 72 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 80 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 80 distinct values High cardinality
image.medium has a high cardinality: 53 distinct values High cardinality
image.original has a high cardinality: 53 distinct values High cardinality
id is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.averageHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.runtimeHigh correlation
_embedded.show.id is highly correlated with id and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.averageHigh correlation
id is highly correlated with _embedded.show.weightHigh correlation
season is highly correlated with number and 1 other fieldsHigh correlation
number is highly correlated with season and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.runtimeHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
id is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.runtimeHigh correlation
_embedded.show.id is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.averageHigh correlation
id is highly correlated with airstamp and 31 other fieldsHigh correlation
season is highly correlated with number and 21 other fieldsHigh correlation
number is highly correlated with season and 22 other fieldsHigh correlation
type is highly correlated with summary and 14 other fieldsHigh correlation
airtime is highly correlated with number and 27 other fieldsHigh correlation
airstamp is highly correlated with id and 35 other fieldsHigh correlation
runtime is highly correlated with id and 31 other fieldsHigh correlation
summary is highly correlated with id and 35 other fieldsHigh correlation
rating.average is highly correlated with id and 29 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 27 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with season and 31 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 37 other fieldsHigh correlation
image.medium is highly correlated with id and 35 other fieldsHigh correlation
image.original is highly correlated with id and 35 other fieldsHigh correlation
number has 6 (4.4%) missing values Missing
runtime has 19 (14.1%) missing values Missing
image has 135 (100.0%) missing values Missing
summary has 90 (66.7%) missing values Missing
rating.average has 112 (83.0%) missing values Missing
_embedded.show.language has 4 (3.0%) missing values Missing
_embedded.show.runtime has 69 (51.1%) missing values Missing
_embedded.show.averageRuntime has 18 (13.3%) missing values Missing
_embedded.show.ended has 87 (64.4%) missing values Missing
_embedded.show.officialSite has 27 (20.0%) missing values Missing
_embedded.show.rating.average has 112 (83.0%) missing values Missing
_embedded.show.network has 135 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 71 (52.6%) missing values Missing
_embedded.show.webChannel.country.code has 71 (52.6%) missing values Missing
_embedded.show.webChannel.country.timezone has 71 (52.6%) missing values Missing
_embedded.show.webChannel.officialSite has 52 (38.5%) missing values Missing
_embedded.show.dvdCountry has 135 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 135 (100.0%) missing values Missing
_embedded.show.externals.thetvdb has 43 (31.9%) missing values Missing
_embedded.show.externals.imdb has 63 (46.7%) missing values Missing
_embedded.show.image.medium has 10 (7.4%) missing values Missing
_embedded.show.image.original has 10 (7.4%) missing values Missing
_embedded.show.summary has 20 (14.8%) missing values Missing
_embedded.show._links.nextepisode.href has 134 (99.3%) missing values Missing
image.medium has 82 (60.7%) missing values Missing
image.original has 82 (60.7%) missing values Missing
_embedded.show.network.id has 134 (99.3%) missing values Missing
_embedded.show.network.name has 134 (99.3%) missing values Missing
_embedded.show.network.country.name has 134 (99.3%) missing values Missing
_embedded.show.network.country.code has 134 (99.3%) missing values Missing
_embedded.show.network.country.timezone has 134 (99.3%) missing values Missing
_embedded.show.network.officialSite has 135 (100.0%) missing values Missing
_embedded.show.webChannel has 135 (100.0%) missing values Missing
_embedded.show.webChannel.country has 135 (100.0%) missing values Missing
_embedded.show.image has 135 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 134 (99.3%) missing values Missing
_embedded.show.dvdCountry.code has 134 (99.3%) missing values Missing
_embedded.show.dvdCountry.timezone has 134 (99.3%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.externals.tvrage is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.weight has 8 (5.9%) zeros Zeros

Reproduction

Analysis started2022-09-05 04:45:12.594056
Analysis finished2022-09-05 04:45:31.848051
Duration19.25 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2065324.519
Minimum1910449
Maximum2353918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:31.903848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1910449
5-th percentile1950007.7
Q11982783
median1993103
Q32161413.5
95-th percentile2323794.3
Maximum2353918
Range443469
Interquartile range (IQR)178630.5

Descriptive statistics

Standard deviation126749.8324
Coefficient of variation (CV)0.06137041963
Kurtosis-0.5257644186
Mean2065324.519
Median Absolute Deviation (MAD)21032
Skewness1.034037259
Sum278818810
Variance1.606552001 × 1010
MonotonicityNot monotonic
2022-09-04T23:45:32.000848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19681151
 
0.7%
19861681
 
0.7%
22404571
 
0.7%
22404561
 
0.7%
22404551
 
0.7%
21972911
 
0.7%
20946671
 
0.7%
20741881
 
0.7%
20722281
 
0.7%
20519851
 
0.7%
Other values (125)125
92.6%
ValueCountFrequency (%)
19104491
0.7%
19248911
0.7%
19500031
0.7%
19500041
0.7%
19500051
0.7%
19500061
0.7%
19500071
0.7%
19500081
0.7%
19500091
0.7%
19504051
0.7%
ValueCountFrequency (%)
23539181
0.7%
23476801
0.7%
23415271
0.7%
23361351
0.7%
23244171
0.7%
23244161
0.7%
23237951
0.7%
23237941
0.7%
23237931
0.7%
22928661
0.7%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-306
 
1
https://www.tvmaze.com/episodes/1986168/the-burning-river-1x18-episode-18
 
1
https://www.tvmaze.com/episodes/2240457/filly-funtasia-2x03-feathers-appear-when-angels-are-near
 
1
https://www.tvmaze.com/episodes/2240456/filly-funtasia-2x02-the-treasure-hunt
 
1
https://www.tvmaze.com/episodes/2240455/filly-funtasia-2x01-the-freshmen
 
1
Other values (130)
130 

Length

Max length171
Median length95
Mean length77.21481481
Min length58

Characters and Unicode

Total characters10424
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-306
2nd rowhttps://www.tvmaze.com/episodes/2121269/fiksiki-4x18-sanki
3rd rowhttps://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin
4th rowhttps://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filme
5th rowhttps://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-5

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-3061
 
0.7%
https://www.tvmaze.com/episodes/1986168/the-burning-river-1x18-episode-181
 
0.7%
https://www.tvmaze.com/episodes/2240457/filly-funtasia-2x03-feathers-appear-when-angels-are-near1
 
0.7%
https://www.tvmaze.com/episodes/2240456/filly-funtasia-2x02-the-treasure-hunt1
 
0.7%
https://www.tvmaze.com/episodes/2240455/filly-funtasia-2x01-the-freshmen1
 
0.7%
https://www.tvmaze.com/episodes/2197291/struggle-meals-1x15-show-me-the-mole1
 
0.7%
https://www.tvmaze.com/episodes/2094667/paradka-1x01-smagcausie-obstoatelstva1
 
0.7%
https://www.tvmaze.com/episodes/2074188/my-lecturer-my-husband-1x03-episode-31
 
0.7%
https://www.tvmaze.com/episodes/2072228/top-dog-fighting-championship-6x01-mihail-sivyj-vs-andrej-panda1
 
0.7%
https://www.tvmaze.com/episodes/2051985/pro-balet-s-nikolaem-ciskaridze-1x31-nikolaj-ciskaridze-pro-balet-vypusk30-golubaa-ptica-russkaa-versia-pro-ballet-part30-sleepingb1
 
0.7%
Other values (125)125
92.6%

Length

2022-09-04T23:45:32.114369image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-3061
 
0.7%
https://www.tvmaze.com/episodes/1976540/var-tid-ar-nu-4x01-forsommar1
 
0.7%
https://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin1
 
0.7%
https://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filme1
 
0.7%
https://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-51
 
0.7%
https://www.tvmaze.com/episodes/2062929/god-of-ten-thousand-realms-1x04-episode-41
 
0.7%
https://www.tvmaze.com/episodes/2353918/300-year-old-class-of-2020-1x05-episode-51
 
0.7%
https://www.tvmaze.com/episodes/2030154/fox-spirit-matchmaker-9x04-episode-1251
 
0.7%
https://www.tvmaze.com/episodes/2324416/unique-lady-2x07-episode-71
 
0.7%
https://www.tvmaze.com/episodes/2324417/unique-lady-2x08-episode-81
 
0.7%
Other values (125)125
92.6%

Most occurring characters

ValueCountFrequency (%)
e839
 
8.0%
-752
 
7.2%
/675
 
6.5%
t659
 
6.3%
s649
 
6.2%
o545
 
5.2%
a455
 
4.4%
w440
 
4.2%
i419
 
4.0%
m391
 
3.8%
Other values (30)4600
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7132
68.4%
Decimal Number1460
 
14.0%
Other Punctuation1080
 
10.4%
Dash Punctuation752
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e839
11.8%
t659
 
9.2%
s649
 
9.1%
o545
 
7.6%
a455
 
6.4%
w440
 
6.2%
i419
 
5.9%
m391
 
5.5%
p377
 
5.3%
d280
 
3.9%
Other values (16)2078
29.1%
Decimal Number
ValueCountFrequency (%)
1278
19.0%
2223
15.3%
0212
14.5%
9156
10.7%
4125
8.6%
598
 
6.7%
895
 
6.5%
393
 
6.4%
691
 
6.2%
789
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/675
62.5%
.270
 
25.0%
:135
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-752
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7132
68.4%
Common3292
31.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e839
11.8%
t659
 
9.2%
s649
 
9.1%
o545
 
7.6%
a455
 
6.4%
w440
 
6.2%
i419
 
5.9%
m391
 
5.5%
p377
 
5.3%
d280
 
3.9%
Other values (16)2078
29.1%
Common
ValueCountFrequency (%)
-752
22.8%
/675
20.5%
1278
 
8.4%
.270
 
8.2%
2223
 
6.8%
0212
 
6.4%
9156
 
4.7%
:135
 
4.1%
4125
 
3.8%
598
 
3.0%
Other values (4)368
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII10424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e839
 
8.0%
-752
 
7.2%
/675
 
6.5%
t659
 
6.3%
s649
 
6.2%
o545
 
5.2%
a455
 
4.4%
w440
 
4.2%
i419
 
4.0%
m391
 
3.8%
Other values (30)4600
44.1%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct121
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Episode 7
 
4
Episode 6
 
4
Episode 4
 
3
Episode 8
 
3
Episode 1
 
2
Other values (116)
119 

Length

Max length96
Median length33
Mean length15.68148148
Min length3

Characters and Unicode

Total characters2117
Distinct characters125
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)83.7%

Sample

1st rowВыпуск 306
2nd rowСанки
3rd row#15 - Даня Милохин
4th rowФильм о фильме
5th rowСерия 5

Common Values

ValueCountFrequency (%)
Episode 74
 
3.0%
Episode 64
 
3.0%
Episode 43
 
2.2%
Episode 83
 
2.2%
Episode 12
 
1.5%
Episode 212
 
1.5%
Episode 32
 
1.5%
Episode 222
 
1.5%
The Spring Ball1
 
0.7%
Funtasia Festival1
 
0.7%
Other values (111)111
82.2%

Length

2022-09-04T23:45:32.224506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode38
 
10.2%
the16
 
4.3%
of10
 
2.7%
i5
 
1.3%
and5
 
1.3%
a5
 
1.3%
65
 
1.3%
34
 
1.1%
74
 
1.1%
24
 
1.1%
Other values (246)276
74.2%

Most occurring characters

ValueCountFrequency (%)
237
 
11.2%
e186
 
8.8%
o123
 
5.8%
i110
 
5.2%
s110
 
5.2%
a96
 
4.5%
r88
 
4.2%
t70
 
3.3%
d64
 
3.0%
n61
 
2.9%
Other values (115)972
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1429
67.5%
Uppercase Letter315
 
14.9%
Space Separator237
 
11.2%
Decimal Number91
 
4.3%
Other Punctuation25
 
1.2%
Dash Punctuation16
 
0.8%
Other Letter2
 
0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e186
13.0%
o123
 
8.6%
i110
 
7.7%
s110
 
7.7%
a96
 
6.7%
r88
 
6.2%
t70
 
4.9%
d64
 
4.5%
n61
 
4.3%
p59
 
4.1%
Other values (48)462
32.3%
Uppercase Letter
ValueCountFrequency (%)
E44
 
14.0%
A25
 
7.9%
T24
 
7.6%
B19
 
6.0%
M19
 
6.0%
S18
 
5.7%
D14
 
4.4%
H13
 
4.1%
C12
 
3.8%
F11
 
3.5%
Other values (32)116
36.8%
Decimal Number
ValueCountFrequency (%)
218
19.8%
116
17.6%
313
14.3%
58
8.8%
77
 
7.7%
67
 
7.7%
47
 
7.7%
07
 
7.7%
86
 
6.6%
92
 
2.2%
Other Punctuation
ValueCountFrequency (%)
.4
16.0%
'4
16.0%
#4
16.0%
,4
16.0%
?3
12.0%
&2
8.0%
:2
8.0%
/1
 
4.0%
!1
 
4.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
237
100.0%
Dash Punctuation
ValueCountFrequency (%)
-16
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1573
74.3%
Common371
 
17.5%
Cyrillic171
 
8.1%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e186
 
11.8%
o123
 
7.8%
i110
 
7.0%
s110
 
7.0%
a96
 
6.1%
r88
 
5.6%
t70
 
4.5%
d64
 
4.1%
n61
 
3.9%
p59
 
3.8%
Other values (42)606
38.5%
Cyrillic
ValueCountFrequency (%)
а16
 
9.4%
и16
 
9.4%
с10
 
5.8%
е8
 
4.7%
л7
 
4.1%
р7
 
4.1%
к7
 
4.1%
т6
 
3.5%
о6
 
3.5%
н6
 
3.5%
Other values (38)82
48.0%
Common
ValueCountFrequency (%)
237
63.9%
218
 
4.9%
-16
 
4.3%
116
 
4.3%
313
 
3.5%
58
 
2.2%
77
 
1.9%
67
 
1.9%
47
 
1.9%
07
 
1.9%
Other values (13)35
 
9.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1935
91.4%
Cyrillic171
 
8.1%
None9
 
0.4%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
237
 
12.2%
e186
 
9.6%
o123
 
6.4%
i110
 
5.7%
s110
 
5.7%
a96
 
5.0%
r88
 
4.5%
t70
 
3.6%
d64
 
3.3%
n61
 
3.2%
Other values (60)790
40.8%
Cyrillic
ValueCountFrequency (%)
а16
 
9.4%
и16
 
9.4%
с10
 
5.8%
е8
 
4.7%
л7
 
4.1%
р7
 
4.1%
к7
 
4.1%
т6
 
3.5%
о6
 
3.5%
н6
 
3.5%
Other values (38)82
48.0%
None
ValueCountFrequency (%)
ø3
33.3%
å2
22.2%
ö2
22.2%
ó1
 
11.1%
ç1
 
11.1%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.28888889
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:32.298743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile9
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation244.6726679
Coefficient of variation (CV)7.577611876
Kurtosis64.92165258
Mean32.28888889
Median Absolute Deviation (MAD)0
Skewness8.121012408
Sum4359
Variance59864.71443
MonotonicityNot monotonic
2022-09-04T23:45:32.365743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
177
57.0%
228
 
20.7%
410
 
7.4%
98
 
5.9%
63
 
2.2%
33
 
2.2%
20202
 
1.5%
51
 
0.7%
171
 
0.7%
181
 
0.7%
ValueCountFrequency (%)
177
57.0%
228
 
20.7%
33
 
2.2%
410
 
7.4%
51
 
0.7%
63
 
2.2%
71
 
0.7%
98
 
5.9%
171
 
0.7%
181
 
0.7%
ValueCountFrequency (%)
20202
 
1.5%
181
 
0.7%
171
 
0.7%
98
 
5.9%
71
 
0.7%
63
 
2.2%
51
 
0.7%
410
 
7.4%
33
 
2.2%
228
20.7%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)24.8%
Missing6
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean12.97674419
Minimum1
Maximum352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:32.447211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q312
95-th percentile33.6
Maximum352
Range351
Interquartile range (IQR)8

Descriptive statistics

Standard deviation32.78420569
Coefficient of variation (CV)2.526381442
Kurtosis90.91309964
Mean12.97674419
Median Absolute Deviation (MAD)3
Skewness8.942148364
Sum1674
Variance1074.804142
MonotonicityNot monotonic
2022-09-04T23:45:32.531210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
414
 
10.4%
512
 
8.9%
112
 
8.9%
612
 
8.9%
211
 
8.1%
711
 
8.1%
39
 
6.7%
87
 
5.2%
93
 
2.2%
153
 
2.2%
Other values (22)35
25.9%
(Missing)6
 
4.4%
ValueCountFrequency (%)
112
8.9%
211
8.1%
39
6.7%
414
10.4%
512
8.9%
612
8.9%
711
8.1%
87
5.2%
93
 
2.2%
103
 
2.2%
ValueCountFrequency (%)
3521
0.7%
871
0.7%
741
0.7%
522
1.5%
351
0.7%
341
0.7%
332
1.5%
312
1.5%
251
0.7%
241
0.7%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
regular
129 
insignificant_special
 
4
significant_special
 
2

Length

Max length21
Median length7
Mean length7.592592593
Min length7

Characters and Unicode

Total characters1025
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowinsignificant_special
5th rowregular

Common Values

ValueCountFrequency (%)
regular129
95.6%
insignificant_special4
 
3.0%
significant_special2
 
1.5%

Length

2022-09-04T23:45:32.622221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:32.703116image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular129
95.6%
insignificant_special4
 
3.0%
significant_special2
 
1.5%

Most occurring characters

ValueCountFrequency (%)
r258
25.2%
a141
13.8%
e135
13.2%
g135
13.2%
l135
13.2%
u129
12.6%
i28
 
2.7%
n16
 
1.6%
s12
 
1.2%
c12
 
1.2%
Other values (4)24
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1019
99.4%
Connector Punctuation6
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r258
25.3%
a141
13.8%
e135
13.2%
g135
13.2%
l135
13.2%
u129
12.7%
i28
 
2.7%
n16
 
1.6%
s12
 
1.2%
c12
 
1.2%
Other values (3)18
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1019
99.4%
Common6
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r258
25.3%
a141
13.8%
e135
13.2%
g135
13.2%
l135
13.2%
u129
12.7%
i28
 
2.7%
n16
 
1.6%
s12
 
1.2%
c12
 
1.2%
Other values (3)18
 
1.8%
Common
ValueCountFrequency (%)
_6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1025
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r258
25.2%
a141
13.8%
e135
13.2%
g135
13.2%
l135
13.2%
u129
12.6%
i28
 
2.7%
n16
 
1.6%
s12
 
1.2%
c12
 
1.2%
Other values (4)24
 
2.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2020-12-25
135 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1350
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-25
2nd row2020-12-25
3rd row2020-12-25
4th row2020-12-25
5th row2020-12-25

Common Values

ValueCountFrequency (%)
2020-12-25135
100.0%

Length

2022-09-04T23:45:32.777122image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:32.850364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-25135
100.0%

Most occurring characters

ValueCountFrequency (%)
2540
40.0%
0270
20.0%
-270
20.0%
1135
 
10.0%
5135
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1080
80.0%
Dash Punctuation270
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2540
50.0%
0270
25.0%
1135
 
12.5%
5135
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2540
40.0%
0270
20.0%
-270
20.0%
1135
 
10.0%
5135
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2540
40.0%
0270
20.0%
-270
20.0%
1135
 
10.0%
5135
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
102 
20:00
11 
12:00
 
7
06:00
 
7
22:00
 
2
Other values (6)
 
6

Length

Max length5
Median length0
Mean length1.222222222
Min length0

Characters and Unicode

Total characters165
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.4%

Sample

1st row
2nd row
3rd row
4th row12:00
5th row12:00

Common Values

ValueCountFrequency (%)
102
75.6%
20:0011
 
8.1%
12:007
 
5.2%
06:007
 
5.2%
22:002
 
1.5%
10:001
 
0.7%
17:001
 
0.7%
21:001
 
0.7%
19:001
 
0.7%
20:451
 
0.7%

Length

2022-09-04T23:45:32.914182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0011
33.3%
12:007
21.2%
06:007
21.2%
22:002
 
6.1%
10:001
 
3.0%
17:001
 
3.0%
21:001
 
3.0%
19:001
 
3.0%
20:451
 
3.0%
00:001
 
3.0%

Most occurring characters

ValueCountFrequency (%)
086
52.1%
:33
 
20.0%
224
 
14.5%
111
 
6.7%
67
 
4.2%
71
 
0.6%
91
 
0.6%
41
 
0.6%
51
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number132
80.0%
Other Punctuation33
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
086
65.2%
224
 
18.2%
111
 
8.3%
67
 
5.3%
71
 
0.8%
91
 
0.8%
41
 
0.8%
51
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
086
52.1%
:33
 
20.0%
224
 
14.5%
111
 
6.7%
67
 
4.2%
71
 
0.6%
91
 
0.6%
41
 
0.6%
51
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
086
52.1%
:33
 
20.0%
224
 
14.5%
111
 
6.7%
67
 
4.2%
71
 
0.6%
91
 
0.6%
41
 
0.6%
51
 
0.6%

airstamp
Categorical

HIGH CORRELATION

Distinct18
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2020-12-25T12:00:00+00:00
76 
2020-12-25T04:00:00+00:00
14 
2020-12-25T11:00:00+00:00
13 
2020-12-25T05:00:00+00:00
 
7
2020-12-25T16:00:00+00:00
 
7
Other values (13)
18 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters3375
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)8.1%

Sample

1st row2020-12-25T00:00:00+00:00
2nd row2020-12-25T00:00:00+00:00
3rd row2020-12-25T00:00:00+00:00
4th row2020-12-25T00:00:00+00:00
5th row2020-12-25T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-25T12:00:00+00:0076
56.3%
2020-12-25T04:00:00+00:0014
 
10.4%
2020-12-25T11:00:00+00:0013
 
9.6%
2020-12-25T05:00:00+00:007
 
5.2%
2020-12-25T16:00:00+00:007
 
5.2%
2020-12-25T00:00:00+00:005
 
3.7%
2020-12-25T17:00:00+00:002
 
1.5%
2020-12-25T15:00:00+00:001
 
0.7%
2020-12-25T13:00:00+00:001
 
0.7%
2020-12-25T12:45:00+00:001
 
0.7%
Other values (8)8
 
5.9%

Length

2022-09-04T23:45:32.988178image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-25t12:00:00+00:0076
56.3%
2020-12-25t04:00:00+00:0014
 
10.4%
2020-12-25t11:00:00+00:0013
 
9.6%
2020-12-25t05:00:00+00:007
 
5.2%
2020-12-25t16:00:00+00:007
 
5.2%
2020-12-25t00:00:00+00:005
 
3.7%
2020-12-25t17:00:00+00:002
 
1.5%
2020-12-25t09:00:00+00:001
 
0.7%
2020-12-25t03:00:00+00:001
 
0.7%
2020-12-25t06:30:00+00:001
 
0.7%
Other values (8)8
 
5.9%

Most occurring characters

ValueCountFrequency (%)
01386
41.1%
2618
18.3%
:405
 
12.0%
-270
 
8.0%
1250
 
7.4%
5143
 
4.2%
T135
 
4.0%
+135
 
4.0%
415
 
0.4%
69
 
0.3%
Other values (4)9
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2430
72.0%
Other Punctuation405
 
12.0%
Dash Punctuation270
 
8.0%
Uppercase Letter135
 
4.0%
Math Symbol135
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01386
57.0%
2618
25.4%
1250
 
10.3%
5143
 
5.9%
415
 
0.6%
69
 
0.4%
34
 
0.2%
73
 
0.1%
91
 
< 0.1%
81
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
:405
100.0%
Dash Punctuation
ValueCountFrequency (%)
-270
100.0%
Uppercase Letter
ValueCountFrequency (%)
T135
100.0%
Math Symbol
ValueCountFrequency (%)
+135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3240
96.0%
Latin135
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01386
42.8%
2618
19.1%
:405
 
12.5%
-270
 
8.3%
1250
 
7.7%
5143
 
4.4%
+135
 
4.2%
415
 
0.5%
69
 
0.3%
34
 
0.1%
Other values (3)5
 
0.2%
Latin
ValueCountFrequency (%)
T135
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01386
41.1%
2618
18.3%
:405
 
12.0%
-270
 
8.0%
1250
 
7.4%
5143
 
4.2%
T135
 
4.0%
+135
 
4.0%
415
 
0.4%
69
 
0.3%
Other values (4)9
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)37.1%
Missing19
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean29.89655172
Minimum1
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:33.070123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.75
Q116.75
median28.5
Q345
95-th percentile60.25
Maximum73
Range72
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation17.87267981
Coefficient of variation (CV)0.5978174332
Kurtosis-1.04874337
Mean29.89655172
Median Absolute Deviation (MAD)16.5
Skewness0.220536616
Sum3468
Variance319.4326837
MonotonicityNot monotonic
2022-09-04T23:45:33.188198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4520
 
14.8%
77
 
5.2%
306
 
4.4%
206
 
4.4%
385
 
3.7%
175
 
3.7%
215
 
3.7%
84
 
3.0%
194
 
3.0%
613
 
2.2%
Other values (33)51
37.8%
(Missing)19
 
14.1%
ValueCountFrequency (%)
11
 
0.7%
43
2.2%
52
 
1.5%
63
2.2%
77
5.2%
84
3.0%
92
 
1.5%
103
2.2%
111
 
0.7%
142
 
1.5%
ValueCountFrequency (%)
731
 
0.7%
641
 
0.7%
621
 
0.7%
613
2.2%
602
1.5%
581
 
0.7%
572
1.5%
551
 
0.7%
531
 
0.7%
503
2.2%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct45
Distinct (%)100.0%
Missing90
Missing (%)66.7%
Memory size1.2 KiB
<p>As friends and families fly their kites, Bheem spots an especially beautiful one. Who does it belong to?</p>
 
1
<p>When Justin tasks Fin with creating an original song to be performed in the film, Fin surprises himself and everyone else when he discovers that his new song is directly connected to one Zach had been writing but was unable to finish before he passed away. Nothing short of a miracle, the story deeply touches Justin and, especially Zach's girlfriend, Amy.</p><p> </p><p> </p>
 
1
<p>Two elderly ladies from St.Petersburg, Russia, who tried to bring a park bench into a trolleybus, immediately hit the headlines and were made into a popular meme after a short video from the shoot had been posted on the Internet. The video turned out to be so absurd and topical that it became a TikTok hit instantaneously and got 100 million views on different social media. After that, it received extensive coverage on the state TV channels, and the main characters of the story became household names all over Russia. The enormous country kept wondering who the women were, why they needed that bench, what was going on, and if that was fake news or not. <br /> </p>
 
1
<p>Super 7 can be traced back to the magazine born out of owner Brian Flynn's love of collecting Kaiju toys. Since then, it's grown into not only a retailer of collectibles &amp; apparel, but also as a producer of esoteric &amp; imaginative products.</p>
 
1
<p>Located in the former Fireplace Shanty of Mays Landing New Jersey is a "Museum of Memories" as Justin and Penelope Daniels like to call it. We know it as Farpoint Toys, one of the most beloved toy stores in America.</p>
 
1
Other values (40)
40 

Length

Max length673
Median length162
Mean length170.6888889
Min length41

Characters and Unicode

Total characters7681
Distinct characters77
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row<p>Randi stubbornly claims that she did not throw Jeanette's Christmas decorations. Bitten doubts the Christmas mood, while August gets barracks fever.</p>
2nd row<p>Summer 1951. The Löwander family is preparing to open a summer restaurant on Gällnö in the Stockholm archipelago. Here Nina meets Calle again, for the first time since she tried to take her life.</p>
3rd row<p>Peter and the other staff prepare the midsummer celebration at the summer restaurant. Chef Backe has high hopes for the evening. Nina and Calle are colleagues, but beneath the surface deeper feelings burn.</p>
4th row<p>Nina moves down to Erik and Christina in Skåne, but it will not be the harmonious reunion she hoped for. Helga suspects that something happened between Nina and Calle on Midsummer's Eve.</p>
5th row<p>Calles and Sonja's marriage is cracking at the seams. In Skåne, Nina sinks deeper into depression. Helga and Backe try to save her. At the restaurant, the closing for the season is approaching.</p>

Common Values

ValueCountFrequency (%)
<p>As friends and families fly their kites, Bheem spots an especially beautiful one. Who does it belong to?</p>1
 
0.7%
<p>When Justin tasks Fin with creating an original song to be performed in the film, Fin surprises himself and everyone else when he discovers that his new song is directly connected to one Zach had been writing but was unable to finish before he passed away. Nothing short of a miracle, the story deeply touches Justin and, especially Zach's girlfriend, Amy.</p><p> </p><p> </p>1
 
0.7%
<p>Two elderly ladies from St.Petersburg, Russia, who tried to bring a park bench into a trolleybus, immediately hit the headlines and were made into a popular meme after a short video from the shoot had been posted on the Internet. The video turned out to be so absurd and topical that it became a TikTok hit instantaneously and got 100 million views on different social media. After that, it received extensive coverage on the state TV channels, and the main characters of the story became household names all over Russia. The enormous country kept wondering who the women were, why they needed that bench, what was going on, and if that was fake news or not. <br /> </p>1
 
0.7%
<p>Super 7 can be traced back to the magazine born out of owner Brian Flynn's love of collecting Kaiju toys. Since then, it's grown into not only a retailer of collectibles &amp; apparel, but also as a producer of esoteric &amp; imaginative products.</p>1
 
0.7%
<p>Located in the former Fireplace Shanty of Mays Landing New Jersey is a "Museum of Memories" as Justin and Penelope Daniels like to call it. We know it as Farpoint Toys, one of the most beloved toy stores in America.</p>1
 
0.7%
<p>Batcave Comics &amp; Toys owners Mike Holbrook &amp; Amanda Barlow share more than just their namesake with the caped crusader, they're both do-gooders in their own right; such as donating comics to local youth charities while under quarantine.</p>1
 
0.7%
<p>Down in Kokomo...Indiana, Todd &amp; Amber Jordan have built one of the most impressive toy stores you'll ever see. With row upon row of exclusives &amp; rarities, Kokomo Toys &amp; Collectibles is the cornerstone of what's become known as "Geek St."</p>1
 
0.7%
<p>Nick Mayor &amp; Jen Lamasters exude the same kind of cool as the Chicago neighborhood their store Bric-A-Brac Records &amp; Toys calls home, Logan Square.</p>1
 
0.7%
<p>When the village's biggest bulls display their strength, can Bheem help his friend, a calf, impress the crowd, too?</p>1
 
0.7%
<p>The villagers are cooking for the festivities, and Bheem wants to show off his culinary skills, too — but he might need some divine intervention!</p>1
 
0.7%
Other values (35)35
 
25.9%
(Missing)90
66.7%

Length

2022-09-04T23:45:33.332270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the62
 
4.9%
to37
 
2.9%
a35
 
2.8%
and34
 
2.7%
of27
 
2.2%
in17
 
1.4%
for16
 
1.3%
p14
 
1.1%
is13
 
1.0%
his12
 
1.0%
Other values (697)988
78.7%

Most occurring characters

ValueCountFrequency (%)
1194
15.5%
e722
 
9.4%
a481
 
6.3%
t470
 
6.1%
o430
 
5.6%
i414
 
5.4%
s411
 
5.4%
n400
 
5.2%
r369
 
4.8%
h284
 
3.7%
Other values (67)2506
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5706
74.3%
Space Separator1210
 
15.8%
Other Punctuation263
 
3.4%
Uppercase Letter242
 
3.2%
Math Symbol232
 
3.0%
Decimal Number17
 
0.2%
Dash Punctuation10
 
0.1%
Initial Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e722
12.7%
a481
 
8.4%
t470
 
8.2%
o430
 
7.5%
i414
 
7.3%
s411
 
7.2%
n400
 
7.0%
r369
 
6.5%
h284
 
5.0%
p216
 
3.8%
Other values (19)1509
26.4%
Uppercase Letter
ValueCountFrequency (%)
S25
 
10.3%
B20
 
8.3%
T19
 
7.9%
A18
 
7.4%
C16
 
6.6%
M15
 
6.2%
D15
 
6.2%
J14
 
5.8%
N11
 
4.5%
I11
 
4.5%
Other values (13)78
32.2%
Other Punctuation
ValueCountFrequency (%)
.76
28.9%
/63
24.0%
,55
20.9%
'26
 
9.9%
;11
 
4.2%
&9
 
3.4%
"9
 
3.4%
?8
 
3.0%
!4
 
1.5%
1
 
0.4%
Decimal Number
ValueCountFrequency (%)
15
29.4%
04
23.5%
23
17.6%
92
 
11.8%
71
 
5.9%
41
 
5.9%
51
 
5.9%
Space Separator
ValueCountFrequency (%)
1194
98.7%
 16
 
1.3%
Math Symbol
ValueCountFrequency (%)
>116
50.0%
<116
50.0%
Dash Punctuation
ValueCountFrequency (%)
-8
80.0%
2
 
20.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5948
77.4%
Common1733
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e722
12.1%
a481
 
8.1%
t470
 
7.9%
o430
 
7.2%
i414
 
7.0%
s411
 
6.9%
n400
 
6.7%
r369
 
6.2%
h284
 
4.8%
p216
 
3.6%
Other values (42)1751
29.4%
Common
ValueCountFrequency (%)
1194
68.9%
>116
 
6.7%
<116
 
6.7%
.76
 
4.4%
/63
 
3.6%
,55
 
3.2%
'26
 
1.5%
 16
 
0.9%
;11
 
0.6%
&9
 
0.5%
Other values (15)51
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7656
99.7%
None21
 
0.3%
Punctuation4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1194
15.6%
e722
 
9.4%
a481
 
6.3%
t470
 
6.1%
o430
 
5.6%
i414
 
5.4%
s411
 
5.4%
n400
 
5.2%
r369
 
4.8%
h284
 
3.7%
Other values (60)2481
32.4%
None
ValueCountFrequency (%)
 16
76.2%
å2
 
9.5%
ö2
 
9.5%
ä1
 
4.8%
Punctuation
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)43.5%
Missing112
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean8.086956522
Minimum7
Maximum9.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:33.573097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7.2
Q17.75
median7.9
Q38.3
95-th percentile9.45
Maximum9.5
Range2.5
Interquartile range (IQR)0.55

Descriptive statistics

Standard deviation0.6890733882
Coefficient of variation (CV)0.08520799962
Kurtosis-0.01711524272
Mean8.086956522
Median Absolute Deviation (MAD)0.2
Skewness0.7227128094
Sum186
Variance0.4748221344
MonotonicityNot monotonic
2022-09-04T23:45:33.655266image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
7.94
 
3.0%
84
 
3.0%
93
 
2.2%
7.82
 
1.5%
7.72
 
1.5%
9.52
 
1.5%
7.22
 
1.5%
8.32
 
1.5%
7.41
 
0.7%
71
 
0.7%
(Missing)112
83.0%
ValueCountFrequency (%)
71
 
0.7%
7.22
1.5%
7.41
 
0.7%
7.72
1.5%
7.82
1.5%
7.94
3.0%
84
3.0%
8.32
1.5%
93
2.2%
9.52
1.5%
ValueCountFrequency (%)
9.52
1.5%
93
2.2%
8.32
1.5%
84
3.0%
7.94
3.0%
7.82
1.5%
7.72
1.5%
7.41
 
0.7%
7.22
1.5%
71
 
0.7%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
https://api.tvmaze.com/episodes/1968115
 
1
https://api.tvmaze.com/episodes/1986168
 
1
https://api.tvmaze.com/episodes/2240457
 
1
https://api.tvmaze.com/episodes/2240456
 
1
https://api.tvmaze.com/episodes/2240455
 
1
Other values (130)
130 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters5265
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1968115
2nd rowhttps://api.tvmaze.com/episodes/2121269
3rd rowhttps://api.tvmaze.com/episodes/1984017
4th rowhttps://api.tvmaze.com/episodes/1991483
5th rowhttps://api.tvmaze.com/episodes/1988016

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19681151
 
0.7%
https://api.tvmaze.com/episodes/19861681
 
0.7%
https://api.tvmaze.com/episodes/22404571
 
0.7%
https://api.tvmaze.com/episodes/22404561
 
0.7%
https://api.tvmaze.com/episodes/22404551
 
0.7%
https://api.tvmaze.com/episodes/21972911
 
0.7%
https://api.tvmaze.com/episodes/20946671
 
0.7%
https://api.tvmaze.com/episodes/20741881
 
0.7%
https://api.tvmaze.com/episodes/20722281
 
0.7%
https://api.tvmaze.com/episodes/20519851
 
0.7%
Other values (125)125
92.6%

Length

2022-09-04T23:45:33.731342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19681151
 
0.7%
https://api.tvmaze.com/episodes/19765401
 
0.7%
https://api.tvmaze.com/episodes/19840171
 
0.7%
https://api.tvmaze.com/episodes/19914831
 
0.7%
https://api.tvmaze.com/episodes/19880161
 
0.7%
https://api.tvmaze.com/episodes/20629291
 
0.7%
https://api.tvmaze.com/episodes/23539181
 
0.7%
https://api.tvmaze.com/episodes/20301541
 
0.7%
https://api.tvmaze.com/episodes/23244161
 
0.7%
https://api.tvmaze.com/episodes/23244171
 
0.7%
Other values (125)125
92.6%

Most occurring characters

ValueCountFrequency (%)
/540
 
10.3%
p405
 
7.7%
s405
 
7.7%
e405
 
7.7%
t405
 
7.7%
a270
 
5.1%
i270
 
5.1%
.270
 
5.1%
m270
 
5.1%
o270
 
5.1%
Other values (16)1755
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3375
64.1%
Other Punctuation945
 
17.9%
Decimal Number945
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p405
12.0%
s405
12.0%
e405
12.0%
t405
12.0%
a270
8.0%
i270
8.0%
m270
8.0%
o270
8.0%
h135
 
4.0%
d135
 
4.0%
Other values (3)405
12.0%
Decimal Number
ValueCountFrequency (%)
1145
15.3%
9142
15.0%
2137
14.5%
095
10.1%
491
9.6%
878
8.3%
568
7.2%
667
7.1%
766
7.0%
356
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/540
57.1%
.270
28.6%
:135
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3375
64.1%
Common1890
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/540
28.6%
.270
14.3%
1145
 
7.7%
9142
 
7.5%
2137
 
7.2%
:135
 
7.1%
095
 
5.0%
491
 
4.8%
878
 
4.1%
568
 
3.6%
Other values (3)189
 
10.0%
Latin
ValueCountFrequency (%)
p405
12.0%
s405
12.0%
e405
12.0%
t405
12.0%
a270
8.0%
i270
8.0%
m270
8.0%
o270
8.0%
h135
 
4.0%
d135
 
4.0%
Other values (3)405
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/540
 
10.3%
p405
 
7.7%
s405
 
7.7%
e405
 
7.7%
t405
 
7.7%
a270
 
5.1%
i270
 
5.1%
.270
 
5.1%
m270
 
5.1%
o270
 
5.1%
Other values (16)1755
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48827.02222
Minimum7847
Maximum62764
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:33.811762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7847
5-th percentile14055
Q145291
median52413
Q355209.5
95-th percentile61237
Maximum62764
Range54917
Interquartile range (IQR)9918.5

Descriptive statistics

Standard deviation12204.32825
Coefficient of variation (CV)0.2499502877
Kurtosis2.558906822
Mean48827.02222
Median Absolute Deviation (MAD)4616
Skewness-1.705106976
Sum6591648
Variance148945628.1
MonotonicityNot monotonic
2022-09-04T23:45:33.898696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5957913
 
9.6%
429668
 
5.9%
140557
 
5.2%
523726
 
4.4%
609495
 
3.7%
326114
 
3.0%
524514
 
3.0%
570293
 
2.2%
519713
 
2.2%
619093
 
2.2%
Other values (70)79
58.5%
ValueCountFrequency (%)
78471
 
0.7%
140557
5.2%
191111
 
0.7%
207341
 
0.7%
225361
 
0.7%
306061
 
0.7%
326114
3.0%
354201
 
0.7%
381711
 
0.7%
381991
 
0.7%
ValueCountFrequency (%)
627641
 
0.7%
625451
 
0.7%
624181
 
0.7%
623061
 
0.7%
619093
 
2.2%
609495
 
3.7%
608091
 
0.7%
596761
 
0.7%
5957913
9.6%
583671
 
0.7%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
https://www.tvmaze.com/shows/59579/filly-funtasia
13 
https://www.tvmaze.com/shows/42966/bridgerton
 
8
https://www.tvmaze.com/shows/14055/letterkenny
 
7
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen
 
6
https://www.tvmaze.com/shows/60949/a-toy-store-near-you
 
5
Other values (75)
96 

Length

Max length68
Median length62
Mean length50.37777778
Min length39

Characters and Unicode

Total characters6801
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)45.2%

Sample

1st rowhttps://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar
2nd rowhttps://www.tvmaze.com/shows/38199/fiksiki
3rd rowhttps://www.tvmaze.com/shows/48288/roast-battle-labelcom
4th rowhttps://www.tvmaze.com/shows/49280/psih
5th rowhttps://www.tvmaze.com/shows/52520/muzskaa-tema

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/59579/filly-funtasia13
 
9.6%
https://www.tvmaze.com/shows/42966/bridgerton8
 
5.9%
https://www.tvmaze.com/shows/14055/letterkenny7
 
5.2%
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen6
 
4.4%
https://www.tvmaze.com/shows/60949/a-toy-store-near-you5
 
3.7%
https://www.tvmaze.com/shows/32611/var-tid-ar-nu4
 
3.0%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.0%
https://www.tvmaze.com/shows/57029/bablo3
 
2.2%
https://www.tvmaze.com/shows/51971/wish-you3
 
2.2%
https://www.tvmaze.com/shows/61909/mighty-little-bheem-kite-festival3
 
2.2%
Other values (70)79
58.5%

Length

2022-09-04T23:45:34.009907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/59579/filly-funtasia13
 
9.6%
https://www.tvmaze.com/shows/42966/bridgerton8
 
5.9%
https://www.tvmaze.com/shows/14055/letterkenny7
 
5.2%
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen6
 
4.4%
https://www.tvmaze.com/shows/60949/a-toy-store-near-you5
 
3.7%
https://www.tvmaze.com/shows/32611/var-tid-ar-nu4
 
3.0%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.0%
https://www.tvmaze.com/shows/57029/bablo3
 
2.2%
https://www.tvmaze.com/shows/51971/wish-you3
 
2.2%
https://www.tvmaze.com/shows/61909/mighty-little-bheem-kite-festival3
 
2.2%
Other values (70)79
58.5%

Most occurring characters

ValueCountFrequency (%)
/675
 
9.9%
t557
 
8.2%
w554
 
8.1%
s493
 
7.2%
o400
 
5.9%
m333
 
4.9%
h324
 
4.8%
e324
 
4.8%
a298
 
4.4%
.270
 
4.0%
Other values (30)2573
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4808
70.7%
Other Punctuation1080
 
15.9%
Decimal Number687
 
10.1%
Dash Punctuation226
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t557
11.6%
w554
11.5%
s493
10.3%
o400
 
8.3%
m333
 
6.9%
h324
 
6.7%
e324
 
6.7%
a298
 
6.2%
p165
 
3.4%
c163
 
3.4%
Other values (16)1197
24.9%
Decimal Number
ValueCountFrequency (%)
5138
20.1%
291
13.2%
979
11.5%
476
11.1%
168
9.9%
666
9.6%
753
 
7.7%
053
 
7.7%
334
 
4.9%
829
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/675
62.5%
.270
 
25.0%
:135
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4808
70.7%
Common1993
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t557
11.6%
w554
11.5%
s493
10.3%
o400
 
8.3%
m333
 
6.9%
h324
 
6.7%
e324
 
6.7%
a298
 
6.2%
p165
 
3.4%
c163
 
3.4%
Other values (16)1197
24.9%
Common
ValueCountFrequency (%)
/675
33.9%
.270
 
13.5%
-226
 
11.3%
5138
 
6.9%
:135
 
6.8%
291
 
4.6%
979
 
4.0%
476
 
3.8%
168
 
3.4%
666
 
3.3%
Other values (4)169
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII6801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/675
 
9.9%
t557
 
8.2%
w554
 
8.1%
s493
 
7.2%
o400
 
5.9%
m333
 
4.9%
h324
 
4.8%
e324
 
4.8%
a298
 
4.4%
.270
 
4.0%
Other values (30)2573
37.8%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Filly Funtasia
13 
Bridgerton
 
8
Letterkenny
 
7
Ida og Martin på Notholmen
 
6
A Toy Store Near You
 
5
Other values (75)
96 

Length

Max length34
Median length26
Mean length15.46666667
Min length4

Characters and Unicode

Total characters2088
Distinct characters94
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)45.2%

Sample

1st rowПо сезону. Видеодайджест Seasonvar
2nd rowФиксики
3rd rowRoast Battle Labelcom
4th rowПсих
5th rowМужская тема

Common Values

ValueCountFrequency (%)
Filly Funtasia13
 
9.6%
Bridgerton8
 
5.9%
Letterkenny7
 
5.2%
Ida og Martin på Notholmen6
 
4.4%
A Toy Store Near You5
 
3.7%
Vår tid är nu4
 
3.0%
The Burning River4
 
3.0%
Bablo3
 
2.2%
Wish You3
 
2.2%
Mighty Little Bheem: Kite Festival3
 
2.2%
Other values (70)79
58.5%

Length

2022-09-04T23:45:34.124511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the15
 
4.2%
funtasia13
 
3.6%
filly13
 
3.6%
you10
 
2.8%
bridgerton8
 
2.2%
a8
 
2.2%
letterkenny7
 
2.0%
ida6
 
1.7%
og6
 
1.7%
martin6
 
1.7%
Other values (179)265
74.2%

Most occurring characters

ValueCountFrequency (%)
222
 
10.6%
e179
 
8.6%
t127
 
6.1%
n126
 
6.0%
i125
 
6.0%
a123
 
5.9%
o120
 
5.7%
r101
 
4.8%
l82
 
3.9%
s59
 
2.8%
Other values (84)824
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1512
72.4%
Uppercase Letter326
 
15.6%
Space Separator222
 
10.6%
Decimal Number13
 
0.6%
Other Punctuation11
 
0.5%
Dash Punctuation4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e179
11.8%
t127
 
8.4%
n126
 
8.3%
i125
 
8.3%
a123
 
8.1%
o120
 
7.9%
r101
 
6.7%
l82
 
5.4%
s59
 
3.9%
u57
 
3.8%
Other values (36)413
27.3%
Uppercase Letter
ValueCountFrequency (%)
F36
 
11.0%
L31
 
9.5%
M24
 
7.4%
T22
 
6.7%
B21
 
6.4%
S21
 
6.4%
N15
 
4.6%
R15
 
4.6%
A13
 
4.0%
Y13
 
4.0%
Other values (29)115
35.3%
Decimal Number
ValueCountFrequency (%)
26
46.2%
05
38.5%
31
 
7.7%
51
 
7.7%
Other Punctuation
ValueCountFrequency (%)
:9
81.8%
,1
 
9.1%
.1
 
9.1%
Space Separator
ValueCountFrequency (%)
222
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1755
84.1%
Common250
 
12.0%
Cyrillic83
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e179
 
10.2%
t127
 
7.2%
n126
 
7.2%
i125
 
7.1%
a123
 
7.0%
o120
 
6.8%
r101
 
5.8%
l82
 
4.7%
s59
 
3.4%
u57
 
3.2%
Other values (44)656
37.4%
Cyrillic
ValueCountFrequency (%)
а10
 
12.0%
и8
 
9.6%
к7
 
8.4%
е7
 
8.4%
с7
 
8.4%
д6
 
7.2%
о4
 
4.8%
р3
 
3.6%
П3
 
3.6%
з2
 
2.4%
Other values (21)26
31.3%
Common
ValueCountFrequency (%)
222
88.8%
:9
 
3.6%
26
 
2.4%
05
 
2.0%
-4
 
1.6%
31
 
0.4%
,1
 
0.4%
.1
 
0.4%
51
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1989
95.3%
Cyrillic83
 
4.0%
None16
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
 
11.2%
e179
 
9.0%
t127
 
6.4%
n126
 
6.3%
i125
 
6.3%
a123
 
6.2%
o120
 
6.0%
r101
 
5.1%
l82
 
4.1%
s59
 
3.0%
Other values (50)725
36.5%
Cyrillic
ValueCountFrequency (%)
а10
 
12.0%
и8
 
9.6%
к7
 
8.4%
е7
 
8.4%
с7
 
8.4%
д6
 
7.2%
о4
 
4.8%
р3
 
3.6%
П3
 
3.6%
з2
 
2.4%
Other values (21)26
31.3%
None
ValueCountFrequency (%)
å10
62.5%
ä5
31.2%
é1
 
6.2%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Scripted
75 
Animation
26 
Documentary
21 
Talk Show
 
4
Variety
 
3
Other values (3)
 
6

Length

Max length11
Median length8
Mean length8.637037037
Min length6

Characters and Unicode

Total characters1166
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTalk Show
2nd rowAnimation
3rd rowGame Show
4th rowScripted
5th rowTalk Show

Common Values

ValueCountFrequency (%)
Scripted75
55.6%
Animation26
 
19.3%
Documentary21
 
15.6%
Talk Show4
 
3.0%
Variety3
 
2.2%
Game Show2
 
1.5%
Reality2
 
1.5%
Sports2
 
1.5%

Length

2022-09-04T23:45:34.210517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:34.295970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted75
53.2%
animation26
 
18.4%
documentary21
 
14.9%
show6
 
4.3%
talk4
 
2.8%
variety3
 
2.1%
game2
 
1.4%
reality2
 
1.4%
sports2
 
1.4%

Most occurring characters

ValueCountFrequency (%)
i132
11.3%
t129
11.1%
e103
8.8%
r101
8.7%
c96
8.2%
S83
 
7.1%
p77
 
6.6%
d75
 
6.4%
n73
 
6.3%
a58
 
5.0%
Other values (16)239
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1019
87.4%
Uppercase Letter141
 
12.1%
Space Separator6
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i132
13.0%
t129
12.7%
e103
10.1%
r101
9.9%
c96
9.4%
p77
7.6%
d75
7.4%
n73
7.2%
a58
5.7%
o55
5.4%
Other values (8)120
11.8%
Uppercase Letter
ValueCountFrequency (%)
S83
58.9%
A26
 
18.4%
D21
 
14.9%
T4
 
2.8%
V3
 
2.1%
G2
 
1.4%
R2
 
1.4%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1160
99.5%
Common6
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i132
11.4%
t129
11.1%
e103
8.9%
r101
8.7%
c96
8.3%
S83
 
7.2%
p77
 
6.6%
d75
 
6.5%
n73
 
6.3%
a58
 
5.0%
Other values (15)233
20.1%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i132
11.3%
t129
11.1%
e103
8.8%
r101
8.7%
c96
8.2%
S83
 
7.1%
p77
 
6.6%
d75
 
6.4%
n73
 
6.3%
a58
 
5.0%
Other values (16)239
20.5%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)11.5%
Missing4
Missing (%)3.0%
Memory size1.2 KiB
English
49 
Chinese
26 
Norwegian
13 
Korean
11 
Russian
10 
Other values (10)
22 

Length

Max length10
Median length7
Mean length7.022900763
Min length4

Characters and Unicode

Total characters920
Distinct characters31
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.1%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English49
36.3%
Chinese26
19.3%
Norwegian13
 
9.6%
Korean11
 
8.1%
Russian10
 
7.4%
Swedish4
 
3.0%
Thai4
 
3.0%
Spanish3
 
2.2%
Tagalog3
 
2.2%
Dutch2
 
1.5%
Other values (5)6
 
4.4%
(Missing)4
 
3.0%

Length

2022-09-04T23:45:34.383036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english49
37.4%
chinese26
19.8%
norwegian13
 
9.9%
korean11
 
8.4%
russian10
 
7.6%
swedish4
 
3.1%
thai4
 
3.1%
spanish3
 
2.3%
tagalog3
 
2.3%
dutch2
 
1.5%
Other values (5)6
 
4.6%

Most occurring characters

ValueCountFrequency (%)
n117
12.7%
i112
12.2%
s105
11.4%
h88
9.6%
e86
9.3%
g70
7.6%
l53
 
5.8%
a51
 
5.5%
E49
 
5.3%
o30
 
3.3%
Other values (21)159
17.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter789
85.8%
Uppercase Letter131
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n117
14.8%
i112
14.2%
s105
13.3%
h88
11.2%
e86
10.9%
g70
8.9%
l53
6.7%
a51
6.5%
o30
 
3.8%
r27
 
3.4%
Other values (8)50
6.3%
Uppercase Letter
ValueCountFrequency (%)
E49
37.4%
C26
19.8%
N13
 
9.9%
K11
 
8.4%
R10
 
7.6%
S7
 
5.3%
T7
 
5.3%
D2
 
1.5%
P2
 
1.5%
M1
 
0.8%
Other values (3)3
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin920
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n117
12.7%
i112
12.2%
s105
11.4%
h88
9.6%
e86
9.3%
g70
7.6%
l53
 
5.8%
a51
 
5.5%
E49
 
5.3%
o30
 
3.3%
Other values (21)159
17.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n117
12.7%
i112
12.2%
s105
11.4%
h88
9.6%
e86
9.3%
g70
7.6%
l53
 
5.8%
a51
 
5.5%
E49
 
5.3%
o30
 
3.3%
Other values (21)159
17.3%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.2 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Running
65 
Ended
48 
To Be Determined
22 

Length

Max length16
Median length7
Mean length7.755555556
Min length5

Characters and Unicode

Total characters1047
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Running65
48.1%
Ended48
35.6%
To Be Determined22
 
16.3%

Length

2022-09-04T23:45:34.454063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:34.526017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
running65
36.3%
ended48
26.8%
to22
 
12.3%
be22
 
12.3%
determined22
 
12.3%

Most occurring characters

ValueCountFrequency (%)
n265
25.3%
e136
13.0%
d118
11.3%
i87
 
8.3%
R65
 
6.2%
u65
 
6.2%
g65
 
6.2%
E48
 
4.6%
44
 
4.2%
T22
 
2.1%
Other values (6)132
12.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter824
78.7%
Uppercase Letter179
 
17.1%
Space Separator44
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n265
32.2%
e136
16.5%
d118
14.3%
i87
 
10.6%
u65
 
7.9%
g65
 
7.9%
o22
 
2.7%
t22
 
2.7%
r22
 
2.7%
m22
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
R65
36.3%
E48
26.8%
T22
 
12.3%
B22
 
12.3%
D22
 
12.3%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1003
95.8%
Common44
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n265
26.4%
e136
13.6%
d118
11.8%
i87
 
8.7%
R65
 
6.5%
u65
 
6.5%
g65
 
6.5%
E48
 
4.8%
T22
 
2.2%
o22
 
2.2%
Other values (5)110
11.0%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n265
25.3%
e136
13.0%
d118
11.3%
i87
 
8.3%
R65
 
6.2%
u65
 
6.2%
g65
 
6.2%
E48
 
4.6%
44
 
4.2%
T22
 
2.1%
Other values (6)132
12.6%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct23
Distinct (%)34.8%
Missing69
Missing (%)51.1%
Infinite0
Infinite (%)0.0%
Mean32.84848485
Minimum1
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:34.593083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q115
median38
Q345
95-th percentile50
Maximum180
Range179
Interquartile range (IQR)30

Descriptive statistics

Standard deviation24.69895197
Coefficient of variation (CV)0.7519053644
Kurtosis18.55450094
Mean32.84848485
Median Absolute Deviation (MAD)11
Skewness3.145726199
Sum2168
Variance610.0382284
MonotonicityNot monotonic
2022-09-04T23:45:34.664083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4516
 
11.9%
407
 
5.2%
306
 
4.4%
105
 
3.7%
504
 
3.0%
383
 
2.2%
253
 
2.2%
203
 
2.2%
52
 
1.5%
42
 
1.5%
Other values (13)15
 
11.1%
(Missing)69
51.1%
ValueCountFrequency (%)
11
 
0.7%
42
 
1.5%
52
 
1.5%
62
 
1.5%
71
 
0.7%
81
 
0.7%
91
 
0.7%
105
3.7%
141
 
0.7%
152
 
1.5%
ValueCountFrequency (%)
1801
 
0.7%
621
 
0.7%
601
 
0.7%
504
 
3.0%
481
 
0.7%
4516
11.9%
407
5.2%
383
 
2.2%
306
 
4.4%
253
 
2.2%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)29.1%
Missing18
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean30.39316239
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:34.742018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q114
median25
Q345
95-th percentile62
Maximum62
Range61
Interquartile range (IQR)31

Descriptive statistics

Standard deviation18.10360855
Coefficient of variation (CV)0.5956474129
Kurtosis-1.151102071
Mean30.39316239
Median Absolute Deviation (MAD)16
Skewness0.2369314498
Sum3556
Variance327.7406425
MonotonicityNot monotonic
2022-09-04T23:45:34.823322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4518
 
13.3%
629
 
6.7%
249
 
6.7%
207
 
5.2%
387
 
5.2%
305
 
3.7%
75
 
3.7%
84
 
3.0%
104
 
3.0%
584
 
3.0%
Other values (24)45
33.3%
(Missing)18
 
13.3%
ValueCountFrequency (%)
11
 
0.7%
42
 
1.5%
52
 
1.5%
63
2.2%
75
3.7%
84
3.0%
91
 
0.7%
104
3.0%
113
2.2%
123
2.2%
ValueCountFrequency (%)
629
6.7%
602
 
1.5%
584
 
3.0%
531
 
0.7%
503
 
2.2%
481
 
0.7%
461
 
0.7%
4518
13.3%
422
 
1.5%
401
 
0.7%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2020-12-25
19 
2019-03-11
13 
2020-12-04
2016-02-07
 
7
2020-12-11
 
6
Other values (56)
81 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1350
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)32.6%

Sample

1st row2015-02-13
2nd row2010-12-13
3rd row2019-12-24
4th row2020-11-05
5th row2020-12-17

Common Values

ValueCountFrequency (%)
2020-12-2519
 
14.1%
2019-03-1113
 
9.6%
2020-12-049
 
6.7%
2016-02-077
 
5.2%
2020-12-116
 
4.4%
2020-12-215
 
3.7%
2020-05-295
 
3.7%
2017-10-024
 
3.0%
2020-12-244
 
3.0%
2019-01-173
 
2.2%
Other values (51)60
44.4%

Length

2022-09-04T23:45:34.914322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2519
 
14.1%
2019-03-1113
 
9.6%
2020-12-049
 
6.7%
2016-02-077
 
5.2%
2020-12-116
 
4.4%
2020-12-215
 
3.7%
2020-05-295
 
3.7%
2017-10-024
 
3.0%
2020-12-244
 
3.0%
2019-01-173
 
2.2%
Other values (51)60
44.4%

Most occurring characters

ValueCountFrequency (%)
2347
25.7%
0329
24.4%
-270
20.0%
1228
16.9%
942
 
3.1%
534
 
2.5%
427
 
2.0%
724
 
1.8%
322
 
1.6%
619
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1080
80.0%
Dash Punctuation270
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2347
32.1%
0329
30.5%
1228
21.1%
942
 
3.9%
534
 
3.1%
427
 
2.5%
724
 
2.2%
322
 
2.0%
619
 
1.8%
88
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2347
25.7%
0329
24.4%
-270
20.0%
1228
16.9%
942
 
3.1%
534
 
2.5%
427
 
2.0%
724
 
1.8%
322
 
1.6%
619
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2347
25.7%
0329
24.4%
-270
20.0%
1228
16.9%
942
 
3.1%
534
 
2.5%
427
 
2.0%
724
 
1.8%
322
 
1.6%
619
 
1.4%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)50.0%
Missing87
Missing (%)64.4%
Memory size1.2 KiB
2020-12-25
10 
2021-01-01
2021-01-07
2021-01-04
 
2
2021-01-02
 
2
Other values (19)
25 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters480
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)27.1%

Sample

1st row2020-12-24
2nd row2020-12-25
3rd row2020-12-28
4th row2021-01-07
5th row2021-01-07

Common Values

ValueCountFrequency (%)
2020-12-2510
 
7.4%
2021-01-015
 
3.7%
2021-01-074
 
3.0%
2021-01-042
 
1.5%
2021-01-022
 
1.5%
2021-01-282
 
1.5%
2020-12-312
 
1.5%
2021-03-122
 
1.5%
2021-01-092
 
1.5%
2021-01-142
 
1.5%
Other values (14)15
 
11.1%
(Missing)87
64.4%

Length

2022-09-04T23:45:34.990115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2510
20.8%
2021-01-015
 
10.4%
2021-01-074
 
8.3%
2021-03-122
 
4.2%
2021-01-292
 
4.2%
2021-01-142
 
4.2%
2021-01-092
 
4.2%
2020-12-312
 
4.2%
2021-01-282
 
4.2%
2021-01-022
 
4.2%
Other values (14)15
31.2%

Most occurring characters

ValueCountFrequency (%)
2141
29.4%
0116
24.2%
-96
20.0%
188
18.3%
513
 
2.7%
45
 
1.0%
85
 
1.0%
95
 
1.0%
74
 
0.8%
34
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number384
80.0%
Dash Punctuation96
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2141
36.7%
0116
30.2%
188
22.9%
513
 
3.4%
45
 
1.3%
85
 
1.3%
95
 
1.3%
74
 
1.0%
34
 
1.0%
63
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2141
29.4%
0116
24.2%
-96
20.0%
188
18.3%
513
 
2.7%
45
 
1.0%
85
 
1.0%
95
 
1.0%
74
 
0.8%
34
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2141
29.4%
0116
24.2%
-96
20.0%
188
18.3%
513
 
2.7%
45
 
1.0%
85
 
1.0%
95
 
1.0%
74
 
0.8%
34
 
0.8%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct69
Distinct (%)63.9%
Missing27
Missing (%)20.0%
Memory size1.2 KiB
https://www.netflix.com/title/80232398
https://www.crave.ca/tv-shows/letterkenny
 
7
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen
 
6
https://www.amazon.com/gp/video/detail/B0891S22PR/
 
5
https://www.svtplay.se/var-tid-ar-nu
 
4
Other values (64)
78 

Length

Max length250
Median length74
Mean length51.02777778
Min length20

Characters and Unicode

Total characters5511
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)50.9%

Sample

1st rowhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html
2nd rowhttp://www.fixiki.ru
3rd rowhttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl3
4th rowhttps://more.tv/psih
5th rowhttps://www.ivi.ru/watch/muzhskaya-tema

Common Values

ValueCountFrequency (%)
https://www.netflix.com/title/802323988
 
5.9%
https://www.crave.ca/tv-shows/letterkenny7
 
5.2%
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen6
 
4.4%
https://www.amazon.com/gp/video/detail/B0891S22PR/5
 
3.7%
https://www.svtplay.se/var-tid-ar-nu4
 
3.0%
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
3.0%
https://www.netflix.com/title/812737283
 
2.2%
https://tv.nrk.no/serie/bablo3
 
2.2%
https://www.viki.com/tv/37486c-wish-you3
 
2.2%
https://www.iq.com/play/1n40eysnffc2
 
1.5%
Other values (59)63
46.7%
(Missing)27
20.0%

Length

2022-09-04T23:45:35.079113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/title/802323988
 
7.4%
https://www.crave.ca/tv-shows/letterkenny7
 
6.5%
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen6
 
5.6%
https://www.amazon.com/gp/video/detail/b0891s22pr5
 
4.6%
https://www.svtplay.se/var-tid-ar-nu4
 
3.7%
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
3.7%
https://www.netflix.com/title/812737283
 
2.8%
https://tv.nrk.no/serie/bablo3
 
2.8%
https://www.viki.com/tv/37486c-wish-you3
 
2.8%
https://www.iqiyi.com/a_19rrhllpip.html2
 
1.9%
Other values (59)63
58.3%

Most occurring characters

ValueCountFrequency (%)
/436
 
7.9%
t425
 
7.7%
w263
 
4.8%
s250
 
4.5%
e233
 
4.2%
.233
 
4.2%
o222
 
4.0%
i214
 
3.9%
a205
 
3.7%
h194
 
3.5%
Other values (65)2836
51.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3540
64.2%
Other Punctuation854
 
15.5%
Decimal Number660
 
12.0%
Uppercase Letter287
 
5.2%
Dash Punctuation101
 
1.8%
Math Symbol36
 
0.7%
Connector Punctuation33
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t425
 
12.0%
w263
 
7.4%
s250
 
7.1%
e233
 
6.6%
o222
 
6.3%
i214
 
6.0%
a205
 
5.8%
h194
 
5.5%
p178
 
5.0%
l160
 
4.5%
Other values (16)1196
33.8%
Uppercase Letter
ValueCountFrequency (%)
P30
 
10.5%
A20
 
7.0%
S20
 
7.0%
N19
 
6.6%
B19
 
6.6%
E16
 
5.6%
R15
 
5.2%
L15
 
5.2%
D14
 
4.9%
C14
 
4.9%
Other values (16)105
36.6%
Decimal Number
ValueCountFrequency (%)
189
13.5%
289
13.5%
872
10.9%
070
10.6%
969
10.5%
361
9.2%
657
8.6%
756
8.5%
454
8.2%
543
6.5%
Other Punctuation
ValueCountFrequency (%)
/436
51.1%
.233
27.3%
:126
 
14.8%
%33
 
3.9%
?17
 
2.0%
&7
 
0.8%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=33
91.7%
+2
 
5.6%
~1
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
-101
100.0%
Connector Punctuation
ValueCountFrequency (%)
_33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3827
69.4%
Common1684
30.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t425
 
11.1%
w263
 
6.9%
s250
 
6.5%
e233
 
6.1%
o222
 
5.8%
i214
 
5.6%
a205
 
5.4%
h194
 
5.1%
p178
 
4.7%
l160
 
4.2%
Other values (42)1483
38.8%
Common
ValueCountFrequency (%)
/436
25.9%
.233
13.8%
:126
 
7.5%
-101
 
6.0%
189
 
5.3%
289
 
5.3%
872
 
4.3%
070
 
4.2%
969
 
4.1%
361
 
3.6%
Other values (13)338
20.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/436
 
7.9%
t425
 
7.7%
w263
 
4.8%
s250
 
4.5%
e233
 
4.2%
.233
 
4.2%
o222
 
4.0%
i214
 
3.9%
a205
 
3.7%
h194
 
3.5%
Other values (65)2836
51.5%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
105 
06:00
 
7
20:00
 
6
12:00
 
4
18:00
 
4
Other values (6)
 
9

Length

Max length5
Median length0
Mean length1.111111111
Min length0

Characters and Unicode

Total characters150
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.0%

Sample

1st row
2nd row
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
105
77.8%
06:007
 
5.2%
20:006
 
4.4%
12:004
 
3.0%
18:004
 
3.0%
19:003
 
2.2%
00:002
 
1.5%
10:001
 
0.7%
17:001
 
0.7%
20:451
 
0.7%

Length

2022-09-04T23:45:35.167377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:007
23.3%
20:006
20.0%
12:004
13.3%
18:004
13.3%
19:003
10.0%
00:002
 
6.7%
10:001
 
3.3%
17:001
 
3.3%
20:451
 
3.3%
22:001
 
3.3%

Most occurring characters

ValueCountFrequency (%)
077
51.3%
:30
 
20.0%
213
 
8.7%
113
 
8.7%
67
 
4.7%
84
 
2.7%
93
 
2.0%
71
 
0.7%
41
 
0.7%
51
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number120
80.0%
Other Punctuation30
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
077
64.2%
213
 
10.8%
113
 
10.8%
67
 
5.8%
84
 
3.3%
93
 
2.5%
71
 
0.8%
41
 
0.8%
51
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
077
51.3%
:30
 
20.0%
213
 
8.7%
113
 
8.7%
67
 
4.7%
84
 
2.7%
93
 
2.0%
71
 
0.7%
41
 
0.7%
51
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
077
51.3%
:30
 
20.0%
213
 
8.7%
113
 
8.7%
67
 
4.7%
84
 
2.7%
93
 
2.0%
71
 
0.7%
41
 
0.7%
51
 
0.7%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.2 KiB

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7
Distinct (%)30.4%
Missing112
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean7.473913043
Minimum5
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:35.237745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.48
Q17.3
median7.3
Q38.2
95-th percentile8.2
Maximum8.2
Range3.2
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.7275221904
Coefficient of variation (CV)0.09734153798
Kurtosis5.239032349
Mean7.473913043
Median Absolute Deviation (MAD)0.2
Skewness-1.775634176
Sum171.9
Variance0.5292885375
MonotonicityNot monotonic
2022-09-04T23:45:35.295804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
7.38
 
5.9%
8.27
 
5.2%
7.23
 
2.2%
7.82
 
1.5%
6.41
 
0.7%
7.51
 
0.7%
51
 
0.7%
(Missing)112
83.0%
ValueCountFrequency (%)
51
 
0.7%
6.41
 
0.7%
7.23
 
2.2%
7.38
5.9%
7.51
 
0.7%
7.82
 
1.5%
8.27
5.2%
ValueCountFrequency (%)
8.27
5.2%
7.82
 
1.5%
7.51
 
0.7%
7.38
5.9%
7.23
 
2.2%
6.41
 
0.7%
51
 
0.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct45
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.31111111
Minimum0
Maximum97
Zeros8
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:35.373774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.5
median27
Q350
95-th percentile97
Maximum97
Range97
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation30.2577156
Coefficient of variation (CV)0.8568893656
Kurtosis-0.4152502295
Mean35.31111111
Median Absolute Deviation (MAD)19
Skewness0.8740723779
Sum4767
Variance915.5293532
MonotonicityNot monotonic
2022-09-04T23:45:35.463774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
714
 
10.4%
239
 
6.7%
978
 
5.9%
08
 
5.9%
957
 
5.2%
47
 
5.2%
307
 
5.2%
206
 
4.4%
386
 
4.4%
114
 
3.0%
Other values (35)59
43.7%
ValueCountFrequency (%)
08
5.9%
21
 
0.7%
32
 
1.5%
47
5.2%
714
10.4%
82
 
1.5%
91
 
0.7%
114
 
3.0%
143
 
2.2%
181
 
0.7%
ValueCountFrequency (%)
978
5.9%
957
5.2%
921
 
0.7%
811
 
0.7%
804
3.0%
771
 
0.7%
761
 
0.7%
751
 
0.7%
691
 
0.7%
682
 
1.5%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct37
Distinct (%)27.6%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean128.8059701
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:35.684656image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median89.5
Q3190
95-th percentile423.1
Maximum516
Range515
Interquartile range (IQR)169

Descriptive statistics

Standard deviation128.3683303
Coefficient of variation (CV)0.9966023329
Kurtosis0.698793113
Mean128.8059701
Median Absolute Deviation (MAD)68.5
Skewness1.244366571
Sum17260
Variance16478.42823
MonotonicityNot monotonic
2022-09-04T23:45:35.772628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
6722
16.3%
2118
13.3%
23811
 
8.1%
111
 
8.1%
1188
 
5.9%
1047
 
5.2%
1097
 
5.2%
35
 
3.7%
2874
 
3.0%
304
 
3.0%
Other values (27)37
27.4%
ValueCountFrequency (%)
111
8.1%
35
 
3.7%
121
 
0.7%
151
 
0.7%
2118
13.3%
304
 
3.0%
512
 
1.5%
561
 
0.7%
6722
16.3%
731
 
0.7%
ValueCountFrequency (%)
5161
0.7%
4641
0.7%
4521
0.7%
4452
1.5%
4402
1.5%
4141
0.7%
4101
0.7%
4051
0.7%
3991
0.7%
3671
0.7%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION

Distinct37
Distinct (%)27.6%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
iQIYI
22 
YouTube
18 
NRK TV
11 
Netflix
11 
Youku
Other values (32)
64 

Length

Max length14
Median length12
Mean length7.126865672
Min length3

Characters and Unicode

Total characters955
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)14.9%

Sample

1st rowSeasonvar
2nd rowYouTube
3rd rowmore.tv
4th rowivi
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
iQIYI22
16.3%
YouTube18
13.3%
NRK TV11
 
8.1%
Netflix11
 
8.1%
Youku8
 
5.9%
Tencent QQ7
 
5.2%
CraveTV7
 
5.2%
Prime Video5
 
3.7%
Disney+4
 
3.0%
Naver TVCast4
 
3.0%
Other values (27)37
27.4%

Length

2022-09-04T23:45:35.860614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
iqiyi22
 
12.5%
youtube18
 
10.2%
tv15
 
8.5%
nrk11
 
6.2%
netflix11
 
6.2%
youku8
 
4.5%
tencent7
 
4.0%
qq7
 
4.0%
cravetv7
 
4.0%
video5
 
2.8%
Other values (37)65
36.9%

Most occurring characters

ValueCountFrequency (%)
e83
 
8.7%
i74
 
7.7%
T61
 
6.4%
u55
 
5.8%
I50
 
5.2%
Y48
 
5.0%
o44
 
4.6%
42
 
4.4%
V41
 
4.3%
a38
 
4.0%
Other values (39)419
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter544
57.0%
Uppercase Letter356
37.3%
Space Separator42
 
4.4%
Math Symbol10
 
1.0%
Other Punctuation3
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e83
15.3%
i74
13.6%
u55
10.1%
o44
 
8.1%
a38
 
7.0%
t35
 
6.4%
r26
 
4.8%
l23
 
4.2%
b22
 
4.0%
n21
 
3.9%
Other values (13)123
22.6%
Uppercase Letter
ValueCountFrequency (%)
T61
17.1%
I50
14.0%
Y48
13.5%
V41
11.5%
Q36
10.1%
N29
8.1%
C17
 
4.8%
S12
 
3.4%
K12
 
3.4%
P12
 
3.4%
Other values (11)38
10.7%
Math Symbol
ValueCountFrequency (%)
+8
80.0%
|2
 
20.0%
Other Punctuation
ValueCountFrequency (%)
.2
66.7%
:1
33.3%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin900
94.2%
Common55
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e83
 
9.2%
i74
 
8.2%
T61
 
6.8%
u55
 
6.1%
I50
 
5.6%
Y48
 
5.3%
o44
 
4.9%
V41
 
4.6%
a38
 
4.2%
Q36
 
4.0%
Other values (34)370
41.1%
Common
ValueCountFrequency (%)
42
76.4%
+8
 
14.5%
|2
 
3.6%
.2
 
3.6%
:1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e83
 
8.7%
i74
 
7.7%
T61
 
6.4%
u55
 
5.8%
I50
 
5.2%
Y48
 
5.0%
o44
 
4.6%
42
 
4.4%
V41
 
4.3%
a38
 
4.0%
Other values (39)419
43.9%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)23.4%
Missing71
Missing (%)52.6%
Memory size1.2 KiB
China
18 
Norway
11 
Canada
Korea, Republic of
Russian Federation
Other values (10)
17 

Length

Max length25
Median length18
Mean length8.609375
Min length5

Characters and Unicode

Total characters551
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowKorea, Republic of

Common Values

ValueCountFrequency (%)
China18
 
13.3%
Norway11
 
8.1%
Canada8
 
5.9%
Korea, Republic of6
 
4.4%
Russian Federation4
 
3.0%
Sweden4
 
3.0%
Taiwan, Province of China2
 
1.5%
Spain2
 
1.5%
Portugal2
 
1.5%
United States2
 
1.5%
Other values (5)5
 
3.7%
(Missing)71
52.6%

Length

2022-09-04T23:45:35.942612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china20
22.7%
norway11
12.5%
canada8
 
9.1%
of8
 
9.1%
korea6
 
6.8%
republic6
 
6.8%
russian4
 
4.5%
federation4
 
4.5%
sweden4
 
4.5%
portugal2
 
2.3%
Other values (10)15
17.0%

Most occurring characters

ValueCountFrequency (%)
a87
15.8%
n51
 
9.3%
i45
 
8.2%
e37
 
6.7%
o33
 
6.0%
C28
 
5.1%
r26
 
4.7%
24
 
4.4%
h22
 
4.0%
d20
 
3.6%
Other values (27)178
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter439
79.7%
Uppercase Letter80
 
14.5%
Space Separator24
 
4.4%
Other Punctuation8
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a87
19.8%
n51
11.6%
i45
10.3%
e37
8.4%
o33
 
7.5%
r26
 
5.9%
h22
 
5.0%
d20
 
4.6%
w17
 
3.9%
t14
 
3.2%
Other values (13)87
19.8%
Uppercase Letter
ValueCountFrequency (%)
C28
35.0%
N12
15.0%
R10
 
12.5%
S8
 
10.0%
K7
 
8.8%
F4
 
5.0%
P4
 
5.0%
T2
 
2.5%
U2
 
2.5%
M1
 
1.2%
Other values (2)2
 
2.5%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
,8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin519
94.2%
Common32
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a87
16.8%
n51
 
9.8%
i45
 
8.7%
e37
 
7.1%
o33
 
6.4%
C28
 
5.4%
r26
 
5.0%
h22
 
4.2%
d20
 
3.9%
w17
 
3.3%
Other values (25)153
29.5%
Common
ValueCountFrequency (%)
24
75.0%
,8
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a87
15.8%
n51
 
9.3%
i45
 
8.2%
e37
 
6.7%
o33
 
6.0%
C28
 
5.1%
r26
 
4.7%
24
 
4.4%
h22
 
4.0%
d20
 
3.6%
Other values (27)178
32.3%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)23.4%
Missing71
Missing (%)52.6%
Memory size1.2 KiB
CN
18 
NO
11 
CA
KR
RU
Other values (10)
17 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters128
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowCN
5th rowKR

Common Values

ValueCountFrequency (%)
CN18
 
13.3%
NO11
 
8.1%
CA8
 
5.9%
KR6
 
4.4%
RU4
 
3.0%
SE4
 
3.0%
TW2
 
1.5%
ES2
 
1.5%
PT2
 
1.5%
US2
 
1.5%
Other values (5)5
 
3.7%
(Missing)71
52.6%

Length

2022-09-04T23:45:36.025660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn18
28.1%
no11
17.2%
ca8
12.5%
kr6
 
9.4%
ru4
 
6.2%
se4
 
6.2%
tw2
 
3.1%
es2
 
3.1%
pt2
 
3.1%
us2
 
3.1%
Other values (5)5
 
7.8%

Most occurring characters

ValueCountFrequency (%)
N31
24.2%
C26
20.3%
O11
 
8.6%
R10
 
7.8%
A8
 
6.2%
S8
 
6.2%
K7
 
5.5%
E7
 
5.5%
U6
 
4.7%
T4
 
3.1%
Other values (8)10
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter128
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N31
24.2%
C26
20.3%
O11
 
8.6%
R10
 
7.8%
A8
 
6.2%
S8
 
6.2%
K7
 
5.5%
E7
 
5.5%
U6
 
4.7%
T4
 
3.1%
Other values (8)10
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
Latin128
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N31
24.2%
C26
20.3%
O11
 
8.6%
R10
 
7.8%
A8
 
6.2%
S8
 
6.2%
K7
 
5.5%
E7
 
5.5%
U6
 
4.7%
T4
 
3.1%
Other values (8)10
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N31
24.2%
C26
20.3%
O11
 
8.6%
R10
 
7.8%
A8
 
6.2%
S8
 
6.2%
K7
 
5.5%
E7
 
5.5%
U6
 
4.7%
T4
 
3.1%
Other values (8)10
 
7.8%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)23.4%
Missing71
Missing (%)52.6%
Memory size1.2 KiB
Asia/Shanghai
18 
Europe/Oslo
11 
America/Halifax
Asia/Seoul
Asia/Kamchatka
Other values (10)
17 

Length

Max length16
Median length15
Mean length12.96875
Min length10

Characters and Unicode

Total characters830
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Shanghai18
 
13.3%
Europe/Oslo11
 
8.1%
America/Halifax8
 
5.9%
Asia/Seoul6
 
4.4%
Asia/Kamchatka4
 
3.0%
Europe/Stockholm4
 
3.0%
Asia/Taipei2
 
1.5%
Europe/Madrid2
 
1.5%
Europe/Lisbon2
 
1.5%
America/New_York2
 
1.5%
Other values (5)5
 
3.7%
(Missing)71
52.6%

Length

2022-09-04T23:45:36.101660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai18
28.1%
europe/oslo11
17.2%
america/halifax8
12.5%
asia/seoul6
 
9.4%
asia/kamchatka4
 
6.2%
europe/stockholm4
 
6.2%
asia/taipei2
 
3.1%
europe/madrid2
 
3.1%
europe/lisbon2
 
3.1%
america/new_york2
 
3.1%
Other values (5)5
 
7.8%

Most occurring characters

ValueCountFrequency (%)
a115
13.9%
i78
 
9.4%
/64
 
7.7%
o52
 
6.3%
s50
 
6.0%
h45
 
5.4%
A44
 
5.3%
e43
 
5.2%
r38
 
4.6%
l32
 
3.9%
Other values (28)269
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter634
76.4%
Uppercase Letter130
 
15.7%
Other Punctuation64
 
7.7%
Connector Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a115
18.1%
i78
12.3%
o52
8.2%
s50
 
7.9%
h45
 
7.1%
e43
 
6.8%
r38
 
6.0%
l32
 
5.0%
u29
 
4.6%
p23
 
3.6%
Other values (13)129
20.3%
Uppercase Letter
ValueCountFrequency (%)
A44
33.8%
S28
21.5%
E21
16.2%
O11
 
8.5%
H8
 
6.2%
K6
 
4.6%
T2
 
1.5%
M2
 
1.5%
L2
 
1.5%
N2
 
1.5%
Other values (3)4
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/64
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin764
92.0%
Common66
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a115
15.1%
i78
 
10.2%
o52
 
6.8%
s50
 
6.5%
h45
 
5.9%
A44
 
5.8%
e43
 
5.6%
r38
 
5.0%
l32
 
4.2%
u29
 
3.8%
Other values (26)238
31.2%
Common
ValueCountFrequency (%)
/64
97.0%
_2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a115
13.9%
i78
 
9.4%
/64
 
7.7%
o52
 
6.3%
s50
 
6.0%
h45
 
5.4%
A44
 
5.3%
e43
 
5.2%
r38
 
4.6%
l32
 
3.9%
Other values (28)269
32.4%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)19.3%
Missing52
Missing (%)38.5%
Memory size1.2 KiB
https://www.iq.com/
22 
https://www.youtube.com
18 
https://www.netflix.com/
11 
https://v.qq.com/
https://www.primevideo.com
Other values (11)
20 

Length

Max length30
Median length26
Mean length21.89156627
Min length17

Characters and Unicode

Total characters1817
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.4%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://www.ivi.ru/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.naver.com/
5th rowhttps://www.iq.com/

Common Values

ValueCountFrequency (%)
https://www.iq.com/22
16.3%
https://www.youtube.com18
 
13.3%
https://www.netflix.com/11
 
8.1%
https://v.qq.com/7
 
5.2%
https://www.primevideo.com5
 
3.7%
https://tv.naver.com/4
 
3.0%
https://www.disneyplus.com/4
 
3.0%
https://www.viki.com/3
 
2.2%
https://www.discoveryplus.com/2
 
1.5%
https://tv.kakao.com/top1
 
0.7%
Other values (6)6
 
4.4%
(Missing)52
38.5%

Length

2022-09-04T23:45:36.180660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.iq.com22
26.5%
https://www.youtube.com18
21.7%
https://www.netflix.com11
13.3%
https://v.qq.com7
 
8.4%
https://www.primevideo.com5
 
6.0%
https://tv.naver.com4
 
4.8%
https://www.disneyplus.com4
 
4.8%
https://www.viki.com3
 
3.6%
https://www.discoveryplus.com2
 
2.4%
https://tv.kakao.com/top1
 
1.2%
Other values (6)6
 
7.2%

Most occurring characters

ValueCountFrequency (%)
/225
12.4%
w213
11.7%
t206
11.3%
.165
 
9.1%
o108
 
5.9%
p97
 
5.3%
s97
 
5.3%
m85
 
4.7%
h83
 
4.6%
:83
 
4.6%
Other values (16)455
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1344
74.0%
Other Punctuation473
 
26.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w213
15.8%
t206
15.3%
o108
8.0%
p97
 
7.2%
s97
 
7.2%
m85
 
6.3%
h83
 
6.2%
c83
 
6.2%
i62
 
4.6%
e54
 
4.0%
Other values (13)256
19.0%
Other Punctuation
ValueCountFrequency (%)
/225
47.6%
.165
34.9%
:83
 
17.5%

Most occurring scripts

ValueCountFrequency (%)
Latin1344
74.0%
Common473
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w213
15.8%
t206
15.3%
o108
8.0%
p97
 
7.2%
s97
 
7.2%
m85
 
6.3%
h83
 
6.2%
c83
 
6.2%
i62
 
4.6%
e54
 
4.0%
Other values (13)256
19.0%
Common
ValueCountFrequency (%)
/225
47.6%
.165
34.9%
:83
 
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/225
12.4%
w213
11.7%
t206
11.3%
.165
 
9.1%
o108
 
5.9%
p97
 
5.3%
s97
 
5.3%
m85
 
4.7%
h83
 
4.6%
:83
 
4.6%
Other values (16)455
25.0%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.externals.tvrage
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct50
Distinct (%)54.3%
Missing43
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean363744.4022
Minimum244021
Maximum410187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:36.264661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum244021
5-th percentile302938
Q1360036.25
median366668
Q3391761.5
95-th percentile395028.15
Maximum410187
Range166166
Interquartile range (IQR)31725.25

Descriptive statistics

Standard deviation34626.98632
Coefficient of variation (CV)0.09519592909
Kurtosis1.326624383
Mean363744.4022
Median Absolute Deviation (MAD)24894
Skewness-1.325362896
Sum33464485
Variance1199028181
MonotonicityNot monotonic
2022-09-04T23:45:36.361661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36051313
 
9.6%
3666688
 
5.9%
3029387
 
5.2%
3847925
 
3.7%
3306064
 
3.0%
3915623
 
2.2%
3957143
 
2.2%
3310952
 
1.5%
3932292
 
1.5%
3940722
 
1.5%
Other values (40)43
31.9%
(Missing)43
31.9%
ValueCountFrequency (%)
2440211
 
0.7%
2651931
 
0.7%
2721571
 
0.7%
2906861
 
0.7%
3029387
5.2%
3103111
 
0.7%
3234201
 
0.7%
3306064
3.0%
3310952
 
1.5%
3366281
 
0.7%
ValueCountFrequency (%)
4101871
 
0.7%
3977341
 
0.7%
3957143
2.2%
3944671
 
0.7%
3940872
1.5%
3940722
1.5%
3939421
 
0.7%
3937431
 
0.7%
3933371
 
0.7%
3932561
 
0.7%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct32
Distinct (%)44.4%
Missing63
Missing (%)46.7%
Memory size1.2 KiB
tt5096624
13 
tt8740790
tt4647692
tt12268838
tt5603140
Other values (27)
35 

Length

Max length10
Median length9
Mean length9.472222222
Min length9

Characters and Unicode

Total characters682
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)29.2%

Sample

1st rowtt3886188
2nd rowtt14125832
3rd rowtt11939550
4th rowtt11939550
5th rowtt8871128

Common Values

ValueCountFrequency (%)
tt509662413
 
9.6%
tt87407908
 
5.9%
tt46476927
 
5.2%
tt122688385
 
3.7%
tt56031404
 
3.0%
tt137110943
 
2.2%
tt122171523
 
2.2%
tt88711282
 
1.5%
tt119395502
 
1.5%
tt135990002
 
1.5%
Other values (22)23
 
17.0%
(Missing)63
46.7%

Length

2022-09-04T23:45:36.456840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt509662413
18.1%
tt87407908
 
11.1%
tt46476927
 
9.7%
tt122688385
 
6.9%
tt56031404
 
5.6%
tt137110943
 
4.2%
tt122171523
 
4.2%
tt135990002
 
2.8%
tt135688762
 
2.8%
tt119395502
 
2.8%
Other values (22)23
31.9%

Most occurring characters

ValueCountFrequency (%)
t144
21.1%
165
9.5%
064
9.4%
263
9.2%
662
9.1%
460
8.8%
856
 
8.2%
948
 
7.0%
745
 
6.6%
341
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number538
78.9%
Lowercase Letter144
 
21.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
165
12.1%
064
11.9%
263
11.7%
662
11.5%
460
11.2%
856
10.4%
948
8.9%
745
8.4%
341
7.6%
534
6.3%
Lowercase Letter
ValueCountFrequency (%)
t144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common538
78.9%
Latin144
 
21.1%

Most frequent character per script

Common
ValueCountFrequency (%)
165
12.1%
064
11.9%
263
11.7%
662
11.5%
460
11.2%
856
10.4%
948
8.9%
745
8.4%
341
7.6%
534
6.3%
Latin
ValueCountFrequency (%)
t144
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t144
21.1%
165
9.5%
064
9.4%
263
9.2%
662
9.1%
460
8.8%
856
 
8.2%
948
 
7.0%
745
 
6.6%
341
 
6.0%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct75
Distinct (%)60.0%
Missing10
Missing (%)7.4%
Memory size1.2 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/385/962619.jpg
13 
https://static.tvmaze.com/uploads/images/medium_portrait/398/995479.jpg
 
8
https://static.tvmaze.com/uploads/images/medium_portrait/290/726561.jpg
 
7
https://static.tvmaze.com/uploads/images/medium_portrait/399/998235.jpg
 
5
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg
 
4
Other values (70)
88 

Length

Max length72
Median length71
Mean length71.032
Min length70

Characters and Unicode

Total characters8879
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)45.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/267/668782.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/295/739859.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/289/723328.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/385/962619.jpg13
 
9.6%
https://static.tvmaze.com/uploads/images/medium_portrait/398/995479.jpg8
 
5.9%
https://static.tvmaze.com/uploads/images/medium_portrait/290/726561.jpg7
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/399/998235.jpg5
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/728621.jpg4
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/407/1019169.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711863.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877136.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/292/731348.jpg2
 
1.5%
Other values (65)73
54.1%
(Missing)10
 
7.4%

Length

2022-09-04T23:45:36.534832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/385/962619.jpg13
 
10.4%
https://static.tvmaze.com/uploads/images/medium_portrait/398/995479.jpg8
 
6.4%
https://static.tvmaze.com/uploads/images/medium_portrait/290/726561.jpg7
 
5.6%
https://static.tvmaze.com/uploads/images/medium_portrait/399/998235.jpg5
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
3.2%
https://static.tvmaze.com/uploads/images/medium_portrait/291/728621.jpg4
 
3.2%
https://static.tvmaze.com/uploads/images/medium_portrait/407/1019169.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711863.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877136.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
1.6%
Other values (65)73
58.4%

Most occurring characters

ValueCountFrequency (%)
/875
 
9.9%
t875
 
9.9%
a625
 
7.0%
m625
 
7.0%
p500
 
5.6%
s500
 
5.6%
i500
 
5.6%
.375
 
4.2%
e375
 
4.2%
o375
 
4.2%
Other values (22)3254
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6250
70.4%
Other Punctuation1375
 
15.5%
Decimal Number1129
 
12.7%
Connector Punctuation125
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t875
14.0%
a625
10.0%
m625
10.0%
p500
 
8.0%
s500
 
8.0%
i500
 
8.0%
e375
 
6.0%
o375
 
6.0%
d250
 
4.0%
u250
 
4.0%
Other values (8)1375
22.0%
Decimal Number
ValueCountFrequency (%)
9177
15.7%
2158
14.0%
7132
11.7%
1129
11.4%
8119
10.5%
3107
9.5%
6103
9.1%
590
8.0%
458
 
5.1%
056
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/875
63.6%
.375
27.3%
:125
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6250
70.4%
Common2629
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t875
14.0%
a625
10.0%
m625
10.0%
p500
 
8.0%
s500
 
8.0%
i500
 
8.0%
e375
 
6.0%
o375
 
6.0%
d250
 
4.0%
u250
 
4.0%
Other values (8)1375
22.0%
Common
ValueCountFrequency (%)
/875
33.3%
.375
14.3%
9177
 
6.7%
2158
 
6.0%
7132
 
5.0%
1129
 
4.9%
_125
 
4.8%
:125
 
4.8%
8119
 
4.5%
3107
 
4.1%
Other values (4)307
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8879
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/875
 
9.9%
t875
 
9.9%
a625
 
7.0%
m625
 
7.0%
p500
 
5.6%
s500
 
5.6%
i500
 
5.6%
.375
 
4.2%
e375
 
4.2%
o375
 
4.2%
Other values (22)3254
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct75
Distinct (%)60.0%
Missing10
Missing (%)7.4%
Memory size1.2 KiB
https://static.tvmaze.com/uploads/images/original_untouched/385/962619.jpg
13 
https://static.tvmaze.com/uploads/images/original_untouched/398/995479.jpg
 
8
https://static.tvmaze.com/uploads/images/original_untouched/290/726561.jpg
 
7
https://static.tvmaze.com/uploads/images/original_untouched/399/998235.jpg
 
5
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg
 
4
Other values (70)
88 

Length

Max length75
Median length74
Mean length74.032
Min length73

Characters and Unicode

Total characters9254
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)45.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/267/668782.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/295/739859.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/723328.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/385/962619.jpg13
 
9.6%
https://static.tvmaze.com/uploads/images/original_untouched/398/995479.jpg8
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726561.jpg7
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/399/998235.jpg5
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/728621.jpg4
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/407/1019169.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/284/711863.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/350/877136.jpg3
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/292/731348.jpg2
 
1.5%
Other values (65)73
54.1%
(Missing)10
 
7.4%

Length

2022-09-04T23:45:36.620833image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/385/962619.jpg13
 
10.4%
https://static.tvmaze.com/uploads/images/original_untouched/398/995479.jpg8
 
6.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/726561.jpg7
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/399/998235.jpg5
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
3.2%
https://static.tvmaze.com/uploads/images/original_untouched/291/728621.jpg4
 
3.2%
https://static.tvmaze.com/uploads/images/original_untouched/407/1019169.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/284/711863.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/350/877136.jpg3
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
1.6%
Other values (65)73
58.4%

Most occurring characters

ValueCountFrequency (%)
/875
 
9.5%
t750
 
8.1%
a625
 
6.8%
s500
 
5.4%
i500
 
5.4%
o500
 
5.4%
p375
 
4.1%
c375
 
4.1%
.375
 
4.1%
g375
 
4.1%
Other values (23)4004
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6625
71.6%
Other Punctuation1375
 
14.9%
Decimal Number1129
 
12.2%
Connector Punctuation125
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t750
 
11.3%
a625
 
9.4%
s500
 
7.5%
i500
 
7.5%
o500
 
7.5%
p375
 
5.7%
c375
 
5.7%
g375
 
5.7%
m375
 
5.7%
e375
 
5.7%
Other values (9)1875
28.3%
Decimal Number
ValueCountFrequency (%)
9177
15.7%
2158
14.0%
7132
11.7%
1129
11.4%
8119
10.5%
3107
9.5%
6103
9.1%
590
8.0%
458
 
5.1%
056
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/875
63.6%
.375
27.3%
:125
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6625
71.6%
Common2629
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t750
 
11.3%
a625
 
9.4%
s500
 
7.5%
i500
 
7.5%
o500
 
7.5%
p375
 
5.7%
c375
 
5.7%
g375
 
5.7%
m375
 
5.7%
e375
 
5.7%
Other values (9)1875
28.3%
Common
ValueCountFrequency (%)
/875
33.3%
.375
14.3%
9177
 
6.7%
2158
 
6.0%
7132
 
5.0%
1129
 
4.9%
:125
 
4.8%
_125
 
4.8%
8119
 
4.5%
3107
 
4.1%
Other values (4)307
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII9254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/875
 
9.5%
t750
 
8.1%
a625
 
6.8%
s500
 
5.4%
i500
 
5.4%
o500
 
5.4%
p375
 
4.1%
c375
 
4.1%
.375
 
4.1%
g375
 
4.1%
Other values (23)4004
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct72
Distinct (%)62.6%
Missing20
Missing (%)14.8%
Memory size1.2 KiB
<p>Based on Julia Quinn's best-selling series of novels, <b>Bridgerton</b> is set in the sexy, lavish and competitive world of Regency London high society. From the glittering ballrooms of Mayfair to the aristocratic palaces of Park Lane and beyond, the series unveils a seductive, sumptuous world replete with intricate rules and dramatic power struggles, where no one is truly ever on steady ground. At the heart of the show is the powerful Bridgerton family. Comprised of eight close-knit siblings, this funny, witty, daring and clever group must navigate the upper ten thousand's marriage mart in search of romance, adventure and love.</p>
 
8
<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>
 
7
<p>Ida and Martin pause city life and move to a small islet on the Romsdal coast. At Notholmen, they will explore an easier way of living.</p>
 
6
<p>Throughout the world, there are hundreds of independently-owned toy stores, each one as unique and endearing as the people that own them. For the loyal customers that flock to them, they're more than simply an outlet to obtain new treasures; they're a community.</p>
 
5
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>
 
4
Other values (67)
85 

Length

Max length1360
Median length569
Mean length407.2521739
Min length54

Characters and Unicode

Total characters46834
Distinct characters97
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)47.0%

Sample

1st row<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>
2nd row<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>
3rd row<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>
4th row<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>
5th row<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>

Common Values

ValueCountFrequency (%)
<p>Based on Julia Quinn's best-selling series of novels, <b>Bridgerton</b> is set in the sexy, lavish and competitive world of Regency London high society. From the glittering ballrooms of Mayfair to the aristocratic palaces of Park Lane and beyond, the series unveils a seductive, sumptuous world replete with intricate rules and dramatic power struggles, where no one is truly ever on steady ground. At the heart of the show is the powerful Bridgerton family. Comprised of eight close-knit siblings, this funny, witty, daring and clever group must navigate the upper ten thousand's marriage mart in search of romance, adventure and love.</p>8
 
5.9%
<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>7
 
5.2%
<p>Ida and Martin pause city life and move to a small islet on the Romsdal coast. At Notholmen, they will explore an easier way of living.</p>6
 
4.4%
<p>Throughout the world, there are hundreds of independently-owned toy stores, each one as unique and endearing as the people that own them. For the loyal customers that flock to them, they're more than simply an outlet to obtain new treasures; they're a community.</p>5
 
3.7%
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
3.0%
<p>The Löwander family operate one of the most prestigious restaurants in Stockholm, exploring what becomes of the establishment as a new era dawns.</p>4
 
3.0%
<p>A free-spirited singer whose love of music has him performing on the streets, Kang In Soo's life revolves completely around music. Supported by his friends, In Soo hopes to someday turn his love of music into a full-time career, but doing so isn't easy. Refusing to give up on his dreams, In Soo continues busking, day in and day out, while his best friend, Choi Min Sung, records his performances and uploads them on YouTube. Little does either of them know that In Soo's performances have caught the attention of someone who could change the young musician's life forever.</p><p>A keyboardist working at a major record company, Yoon Sang Yi is always on the lookout for new talent. After stumbling upon In Soo's videos, Sang Yi has become one of the singer's biggest fans. Convinced In Soo could make it big, he recommends the young artist join his company's rookie discovery project. Seeing this opportunity in this invitation, In Soo accepts the offer and soon moves into the company residence with Sang Yi.</p><p>As the two live and work together, their relationship grows and slowly, new feelings begin to blossom. Unfortunately, as their feelings grow, so do the obstacles that stand in their way. Will In Soo and Sang Yi be able to find a way to overcome the trials before them or will their love fade before ever having a chance to fully bloom?</p>3
 
2.2%
<p>With winter behind them, Bheem and his townspeople usher in a sunny new season in all their favorite ways during the Makar Sankranti festival.</p>3
 
2.2%
<p>Welcome to <b>Bablo</b>, the world's best library!</p>3
 
2.2%
<p>The disciples of the Lingchuan Sect have guarded the Fans of Heaven and Earth for nearly a century. Mu Yun and Hua Yue are the only disciples of the sect that are left. The stubborn and disobedient Hua Yue unintentionally discovers that the Fan of Heaven possesses the power to travel through time. To escape being forced to study and practice martial arts by Mu Yun, Hua Yue travels to the future to have fun. Hundreds of years in the future she meets Xiao Qian who looks exactly like her. Secrets come to the surface, and adventures take place.</p>2
 
1.5%
Other values (62)70
51.9%
(Missing)20
 
14.8%

Length

2022-09-04T23:45:36.729567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the478
 
6.1%
of274
 
3.5%
and252
 
3.2%
a217
 
2.8%
to203
 
2.6%
in163
 
2.1%
is98
 
1.3%
with75
 
1.0%
on72
 
0.9%
his69
 
0.9%
Other values (1841)5934
75.7%

Most occurring characters

ValueCountFrequency (%)
7709
16.5%
e4420
 
9.4%
t3015
 
6.4%
o2852
 
6.1%
n2765
 
5.9%
a2700
 
5.8%
i2542
 
5.4%
s2296
 
4.9%
r2196
 
4.7%
h1821
 
3.9%
Other values (87)14518
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter35546
75.9%
Space Separator7721
 
16.5%
Other Punctuation1301
 
2.8%
Uppercase Letter1269
 
2.7%
Math Symbol775
 
1.7%
Dash Punctuation98
 
0.2%
Decimal Number85
 
0.2%
Open Punctuation13
 
< 0.1%
Close Punctuation13
 
< 0.1%
Format12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4420
12.4%
t3015
 
8.5%
o2852
 
8.0%
n2765
 
7.8%
a2700
 
7.6%
i2542
 
7.2%
s2296
 
6.5%
r2196
 
6.2%
h1821
 
5.1%
l1501
 
4.2%
Other values (28)9438
26.6%
Uppercase Letter
ValueCountFrequency (%)
S128
 
10.1%
T105
 
8.3%
L93
 
7.3%
W93
 
7.3%
A92
 
7.2%
B60
 
4.7%
M59
 
4.6%
I58
 
4.6%
Y57
 
4.5%
C56
 
4.4%
Other values (18)468
36.9%
Other Punctuation
ValueCountFrequency (%)
,484
37.2%
.389
29.9%
/203
15.6%
'112
 
8.6%
"39
 
3.0%
!21
 
1.6%
:20
 
1.5%
;18
 
1.4%
?14
 
1.1%
&1
 
0.1%
Decimal Number
ValueCountFrequency (%)
026
30.6%
116
18.8%
216
18.8%
36
 
7.1%
45
 
5.9%
95
 
5.9%
84
 
4.7%
54
 
4.7%
73
 
3.5%
Math Symbol
ValueCountFrequency (%)
>387
49.9%
<387
49.9%
+1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-89
90.8%
7
 
7.1%
2
 
2.0%
Space Separator
ValueCountFrequency (%)
7709
99.8%
 12
 
0.2%
Open Punctuation
ValueCountFrequency (%)
(13
100.0%
Close Punctuation
ValueCountFrequency (%)
)13
100.0%
Format
ValueCountFrequency (%)
12
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin36804
78.6%
Common10019
 
21.4%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4420
12.0%
t3015
 
8.2%
o2852
 
7.7%
n2765
 
7.5%
a2700
 
7.3%
i2542
 
6.9%
s2296
 
6.2%
r2196
 
6.0%
h1821
 
4.9%
l1501
 
4.1%
Other values (46)10696
29.1%
Common
ValueCountFrequency (%)
7709
76.9%
,484
 
4.8%
.389
 
3.9%
>387
 
3.9%
<387
 
3.9%
/203
 
2.0%
'112
 
1.1%
-89
 
0.9%
"39
 
0.4%
026
 
0.3%
Other values (21)194
 
1.9%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
у1
9.1%
ж1
9.1%
с1
9.1%
к1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%
М1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII46780
99.9%
None22
 
< 0.1%
Punctuation21
 
< 0.1%
Cyrillic11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7709
16.5%
e4420
 
9.4%
t3015
 
6.4%
o2852
 
6.1%
n2765
 
5.9%
a2700
 
5.8%
i2542
 
5.4%
s2296
 
4.9%
r2196
 
4.7%
h1821
 
3.9%
Other values (69)14464
30.9%
Punctuation
ValueCountFrequency (%)
12
57.1%
7
33.3%
2
 
9.5%
None
ValueCountFrequency (%)
 12
54.5%
ö4
 
18.2%
Í3
 
13.6%
ä2
 
9.1%
á1
 
4.5%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
у1
9.1%
ж1
9.1%
с1
9.1%
к1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%
М1
9.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1641076505
Minimum1604587145
Maximum1662307326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2022-09-04T23:45:36.834661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1604587145
5-th percentile1609378127
Q11631482776
median1647025026
Q31653500557
95-th percentile1661115158
Maximum1662307326
Range57720181
Interquartile range (IQR)22017780.5

Descriptive statistics

Standard deviation16015417.43
Coefficient of variation (CV)0.009759092512
Kurtosis-0.6362320257
Mean1641076505
Median Absolute Deviation (MAD)7568125
Skewness-0.7726484318
Sum2.215453282 × 1011
Variance2.564935956 × 1014
MonotonicityNot monotonic
2022-09-04T23:45:36.930739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
164001309513
 
9.6%
16502801058
 
5.9%
16475629267
 
5.2%
16090087126
 
4.4%
16470250265
 
3.7%
16208994464
 
3.0%
16545931514
 
3.0%
16342924673
 
2.2%
16550008103
 
2.2%
16520392983
 
2.2%
Other values (70)79
58.5%
ValueCountFrequency (%)
16045871451
 
0.7%
16090087126
4.4%
16095364481
 
0.7%
16103080041
 
0.7%
16119763811
 
0.7%
16125166641
 
0.7%
16129809601
 
0.7%
16130883481
 
0.7%
16140886071
 
0.7%
16141009141
 
0.7%
ValueCountFrequency (%)
16623073261
0.7%
16623062101
0.7%
16622908591
0.7%
16615205871
0.7%
16613636441
0.7%
16613414631
0.7%
16611783501
0.7%
16610880751
0.7%
16609296881
0.7%
16602618862
1.5%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
https://api.tvmaze.com/shows/59579
13 
https://api.tvmaze.com/shows/42966
 
8
https://api.tvmaze.com/shows/14055
 
7
https://api.tvmaze.com/shows/52372
 
6
https://api.tvmaze.com/shows/60949
 
5
Other values (75)
96 

Length

Max length34
Median length34
Mean length33.99259259
Min length33

Characters and Unicode

Total characters4589
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)45.2%

Sample

1st rowhttps://api.tvmaze.com/shows/7847
2nd rowhttps://api.tvmaze.com/shows/38199
3rd rowhttps://api.tvmaze.com/shows/48288
4th rowhttps://api.tvmaze.com/shows/49280
5th rowhttps://api.tvmaze.com/shows/52520

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5957913
 
9.6%
https://api.tvmaze.com/shows/429668
 
5.9%
https://api.tvmaze.com/shows/140557
 
5.2%
https://api.tvmaze.com/shows/523726
 
4.4%
https://api.tvmaze.com/shows/609495
 
3.7%
https://api.tvmaze.com/shows/326114
 
3.0%
https://api.tvmaze.com/shows/524514
 
3.0%
https://api.tvmaze.com/shows/570293
 
2.2%
https://api.tvmaze.com/shows/519713
 
2.2%
https://api.tvmaze.com/shows/619093
 
2.2%
Other values (70)79
58.5%

Length

2022-09-04T23:45:37.024911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5957913
 
9.6%
https://api.tvmaze.com/shows/429668
 
5.9%
https://api.tvmaze.com/shows/140557
 
5.2%
https://api.tvmaze.com/shows/523726
 
4.4%
https://api.tvmaze.com/shows/609495
 
3.7%
https://api.tvmaze.com/shows/326114
 
3.0%
https://api.tvmaze.com/shows/524514
 
3.0%
https://api.tvmaze.com/shows/570293
 
2.2%
https://api.tvmaze.com/shows/519713
 
2.2%
https://api.tvmaze.com/shows/619093
 
2.2%
Other values (70)79
58.5%

Most occurring characters

ValueCountFrequency (%)
/540
 
11.8%
s405
 
8.8%
t405
 
8.8%
h270
 
5.9%
p270
 
5.9%
a270
 
5.9%
.270
 
5.9%
o270
 
5.9%
m270
 
5.9%
5137
 
3.0%
Other values (16)1482
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2970
64.7%
Other Punctuation945
 
20.6%
Decimal Number674
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s405
13.6%
t405
13.6%
h270
9.1%
p270
9.1%
a270
9.1%
o270
9.1%
m270
9.1%
e135
 
4.5%
w135
 
4.5%
c135
 
4.5%
Other values (3)405
13.6%
Decimal Number
ValueCountFrequency (%)
5137
20.3%
285
12.6%
979
11.7%
476
11.3%
168
10.1%
666
9.8%
753
 
7.9%
048
 
7.1%
333
 
4.9%
829
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/540
57.1%
.270
28.6%
:135
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2970
64.7%
Common1619
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/540
33.4%
.270
16.7%
5137
 
8.5%
:135
 
8.3%
285
 
5.3%
979
 
4.9%
476
 
4.7%
168
 
4.2%
666
 
4.1%
753
 
3.3%
Other values (3)110
 
6.8%
Latin
ValueCountFrequency (%)
s405
13.6%
t405
13.6%
h270
9.1%
p270
9.1%
a270
9.1%
o270
9.1%
m270
9.1%
e135
 
4.5%
w135
 
4.5%
c135
 
4.5%
Other values (3)405
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/540
 
11.8%
s405
 
8.8%
t405
 
8.8%
h270
 
5.9%
p270
 
5.9%
a270
 
5.9%
.270
 
5.9%
o270
 
5.9%
m270
 
5.9%
5137
 
3.0%
Other values (16)1482
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct80
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
https://api.tvmaze.com/episodes/2240467
13 
https://api.tvmaze.com/episodes/2298229
 
8
https://api.tvmaze.com/episodes/2294357
 
7
https://api.tvmaze.com/episodes/1993103
 
6
https://api.tvmaze.com/episodes/2292876
 
5
Other values (75)
96 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters5265
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)45.2%

Sample

1st rowhttps://api.tvmaze.com/episodes/2338362
2nd rowhttps://api.tvmaze.com/episodes/2370911
3rd rowhttps://api.tvmaze.com/episodes/2362860
4th rowhttps://api.tvmaze.com/episodes/1960733
5th rowhttps://api.tvmaze.com/episodes/1988016

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/224046713
 
9.6%
https://api.tvmaze.com/episodes/22982298
 
5.9%
https://api.tvmaze.com/episodes/22943577
 
5.2%
https://api.tvmaze.com/episodes/19931036
 
4.4%
https://api.tvmaze.com/episodes/22928765
 
3.7%
https://api.tvmaze.com/episodes/19765434
 
3.0%
https://api.tvmaze.com/episodes/19861744
 
3.0%
https://api.tvmaze.com/episodes/21538673
 
2.2%
https://api.tvmaze.com/episodes/19748243
 
2.2%
https://api.tvmaze.com/episodes/23237953
 
2.2%
Other values (70)79
58.5%

Length

2022-09-04T23:45:37.101907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/224046713
 
9.6%
https://api.tvmaze.com/episodes/22982298
 
5.9%
https://api.tvmaze.com/episodes/22943577
 
5.2%
https://api.tvmaze.com/episodes/19931036
 
4.4%
https://api.tvmaze.com/episodes/22928765
 
3.7%
https://api.tvmaze.com/episodes/19765434
 
3.0%
https://api.tvmaze.com/episodes/19861744
 
3.0%
https://api.tvmaze.com/episodes/21538673
 
2.2%
https://api.tvmaze.com/episodes/19748243
 
2.2%
https://api.tvmaze.com/episodes/23237953
 
2.2%
Other values (70)79
58.5%

Most occurring characters

ValueCountFrequency (%)
/540
 
10.3%
t405
 
7.7%
p405
 
7.7%
s405
 
7.7%
e405
 
7.7%
a270
 
5.1%
i270
 
5.1%
.270
 
5.1%
m270
 
5.1%
o270
 
5.1%
Other values (16)1755
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3375
64.1%
Other Punctuation945
 
17.9%
Decimal Number945
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t405
12.0%
p405
12.0%
s405
12.0%
e405
12.0%
a270
8.0%
i270
8.0%
m270
8.0%
o270
8.0%
h135
 
4.0%
d135
 
4.0%
Other values (3)405
12.0%
Decimal Number
ValueCountFrequency (%)
2201
21.3%
9120
12.7%
7101
10.7%
486
9.1%
186
9.1%
384
8.9%
069
 
7.3%
667
 
7.1%
867
 
7.1%
564
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/540
57.1%
.270
28.6%
:135
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3375
64.1%
Common1890
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/540
28.6%
.270
14.3%
2201
 
10.6%
:135
 
7.1%
9120
 
6.3%
7101
 
5.3%
486
 
4.6%
186
 
4.6%
384
 
4.4%
069
 
3.7%
Other values (3)198
 
10.5%
Latin
ValueCountFrequency (%)
t405
12.0%
p405
12.0%
s405
12.0%
e405
12.0%
a270
8.0%
i270
8.0%
m270
8.0%
o270
8.0%
h135
 
4.0%
d135
 
4.0%
Other values (3)405
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/540
 
10.3%
t405
 
7.7%
p405
 
7.7%
s405
 
7.7%
e405
 
7.7%
a270
 
5.1%
i270
 
5.1%
.270
 
5.1%
m270
 
5.1%
o270
 
5.1%
Other values (16)1755
33.3%

_embedded.show._links.nextepisode.href
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
https://api.tvmaze.com/episodes/2338363

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2338363

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:37.175900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:37.246912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
100.0%

Most occurring characters

ValueCountFrequency (%)
/4
 
10.3%
34
 
10.3%
p3
 
7.7%
s3
 
7.7%
t3
 
7.7%
e3
 
7.7%
m2
 
5.1%
o2
 
5.1%
a2
 
5.1%
i2
 
5.1%
Other values (10)11
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25
64.1%
Other Punctuation7
 
17.9%
Decimal Number7
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p3
12.0%
s3
12.0%
t3
12.0%
e3
12.0%
m2
8.0%
o2
8.0%
a2
8.0%
i2
8.0%
d1
 
4.0%
h1
 
4.0%
Other values (3)3
12.0%
Decimal Number
ValueCountFrequency (%)
34
57.1%
81
 
14.3%
21
 
14.3%
61
 
14.3%
Other Punctuation
ValueCountFrequency (%)
/4
57.1%
.2
28.6%
:1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin25
64.1%
Common14
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
p3
12.0%
s3
12.0%
t3
12.0%
e3
12.0%
m2
8.0%
o2
8.0%
a2
8.0%
i2
8.0%
d1
 
4.0%
h1
 
4.0%
Other values (3)3
12.0%
Common
ValueCountFrequency (%)
/4
28.6%
34
28.6%
.2
14.3%
81
 
7.1%
21
 
7.1%
:1
 
7.1%
61
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/4
 
10.3%
34
 
10.3%
p3
 
7.7%
s3
 
7.7%
t3
 
7.7%
e3
 
7.7%
m2
 
5.1%
o2
 
5.1%
a2
 
5.1%
i2
 
5.1%
Other values (10)11
28.2%

image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct53
Distinct (%)100.0%
Missing82
Missing (%)60.7%
Memory size1.2 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/290/726645.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726578.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726629.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/729312.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/727232.jpg
 
1
Other values (48)
48 

Length

Max length73
Median length72
Mean length72.01886792
Min length72

Characters and Unicode

Total characters3817
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/353/883109.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/410/1026277.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/393/983022.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/393/983023.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/295/738238.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726645.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726578.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726629.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729312.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727232.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728783.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727777.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/293/732804.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726584.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726632.jpg1
 
0.7%
Other values (43)43
31.9%
(Missing)82
60.7%

Length

2022-09-04T23:45:37.315214image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726645.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726551.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/410/1026277.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/393/983022.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/393/983023.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/295/738238.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714188.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726879.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726880.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726881.jpg1
 
1.9%
Other values (43)43
81.1%

Most occurring characters

ValueCountFrequency (%)
/371
 
9.7%
a318
 
8.3%
s265
 
6.9%
m265
 
6.9%
t265
 
6.9%
p212
 
5.6%
e212
 
5.6%
i159
 
4.2%
c159
 
4.2%
.159
 
4.2%
Other values (22)1432
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2703
70.8%
Other Punctuation583
 
15.3%
Decimal Number478
 
12.5%
Connector Punctuation53
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a318
11.8%
s265
9.8%
m265
9.8%
t265
9.8%
p212
 
7.8%
e212
 
7.8%
i159
 
5.9%
c159
 
5.9%
d159
 
5.9%
u106
 
3.9%
Other values (8)583
21.6%
Decimal Number
ValueCountFrequency (%)
2107
22.4%
766
13.8%
958
12.1%
047
9.8%
646
9.6%
544
9.2%
339
 
8.2%
836
 
7.5%
120
 
4.2%
415
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/371
63.6%
.159
27.3%
:53
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2703
70.8%
Common1114
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a318
11.8%
s265
9.8%
m265
9.8%
t265
9.8%
p212
 
7.8%
e212
 
7.8%
i159
 
5.9%
c159
 
5.9%
d159
 
5.9%
u106
 
3.9%
Other values (8)583
21.6%
Common
ValueCountFrequency (%)
/371
33.3%
.159
14.3%
2107
 
9.6%
766
 
5.9%
958
 
5.2%
_53
 
4.8%
:53
 
4.8%
047
 
4.2%
646
 
4.1%
544
 
3.9%
Other values (4)110
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/371
 
9.7%
a318
 
8.3%
s265
 
6.9%
m265
 
6.9%
t265
 
6.9%
p212
 
5.6%
e212
 
5.6%
i159
 
4.2%
c159
 
4.2%
.159
 
4.2%
Other values (22)1432
37.5%

image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct53
Distinct (%)100.0%
Missing82
Missing (%)60.7%
Memory size1.2 KiB
https://static.tvmaze.com/uploads/images/original_untouched/290/726645.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726578.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726629.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/729312.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/727232.jpg
 
1
Other values (48)
48 

Length

Max length75
Median length74
Mean length74.01886792
Min length74

Characters and Unicode

Total characters3923
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/353/883109.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/410/1026277.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/393/983022.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/393/983023.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/295/738238.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726645.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726578.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726629.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729312.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/727232.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/728783.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/727777.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/293/732804.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726584.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726632.jpg1
 
0.7%
Other values (43)43
31.9%
(Missing)82
60.7%

Length

2022-09-04T23:45:37.391436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726645.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726551.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/410/1026277.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/393/983022.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/393/983023.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/295/738238.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/285/714188.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726879.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726880.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726881.jpg1
 
1.9%
Other values (43)43
81.1%

Most occurring characters

ValueCountFrequency (%)
/371
 
9.5%
t318
 
8.1%
a265
 
6.8%
s212
 
5.4%
o212
 
5.4%
i212
 
5.4%
m159
 
4.1%
u159
 
4.1%
e159
 
4.1%
g159
 
4.1%
Other values (23)1697
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2809
71.6%
Other Punctuation583
 
14.9%
Decimal Number478
 
12.2%
Connector Punctuation53
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t318
 
11.3%
a265
 
9.4%
s212
 
7.5%
o212
 
7.5%
i212
 
7.5%
m159
 
5.7%
u159
 
5.7%
e159
 
5.7%
g159
 
5.7%
c159
 
5.7%
Other values (9)795
28.3%
Decimal Number
ValueCountFrequency (%)
2107
22.4%
766
13.8%
958
12.1%
047
9.8%
646
9.6%
544
9.2%
339
 
8.2%
836
 
7.5%
120
 
4.2%
415
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/371
63.6%
.159
27.3%
:53
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2809
71.6%
Common1114
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t318
 
11.3%
a265
 
9.4%
s212
 
7.5%
o212
 
7.5%
i212
 
7.5%
m159
 
5.7%
u159
 
5.7%
e159
 
5.7%
g159
 
5.7%
c159
 
5.7%
Other values (9)795
28.3%
Common
ValueCountFrequency (%)
/371
33.3%
.159
14.3%
2107
 
9.6%
766
 
5.9%
958
 
5.2%
_53
 
4.8%
:53
 
4.8%
047
 
4.2%
646
 
4.1%
544
 
3.9%
Other values (4)110
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/371
 
9.5%
t318
 
8.1%
a265
 
6.8%
s212
 
5.4%
o212
 
5.4%
i212
 
5.4%
m159
 
4.1%
u159
 
4.1%
e159
 
4.1%
g159
 
4.1%
Other values (23)1697
43.3%

_embedded.show.network.id
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
239.0

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row239.0

Common Values

ValueCountFrequency (%)
239.01
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:37.466435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:37.530726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
239.01
100.0%

Most occurring characters

ValueCountFrequency (%)
21
20.0%
31
20.0%
91
20.0%
.1
20.0%
01
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
80.0%
Other Punctuation1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
21
25.0%
31
25.0%
91
25.0%
01
25.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
21
20.0%
31
20.0%
91
20.0%
.1
20.0%
01
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
20.0%
31
20.0%
91
20.0%
.1
20.0%
01
20.0%

_embedded.show.network.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
Россия 1

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowРоссия 1

Common Values

ValueCountFrequency (%)
Россия 11
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:37.607064image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:37.832676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
россия1
50.0%
11
50.0%

Most occurring characters

ValueCountFrequency (%)
с2
25.0%
Р1
12.5%
о1
12.5%
и1
12.5%
я1
12.5%
1
12.5%
11
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5
62.5%
Uppercase Letter1
 
12.5%
Space Separator1
 
12.5%
Decimal Number1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
с2
40.0%
о1
20.0%
и1
20.0%
я1
20.0%
Uppercase Letter
ValueCountFrequency (%)
Р1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic6
75.0%
Common2
 
25.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
с2
33.3%
Р1
16.7%
о1
16.7%
и1
16.7%
я1
16.7%
Common
ValueCountFrequency (%)
1
50.0%
11
50.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic6
75.0%
ASCII2
 
25.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
с2
33.3%
Р1
16.7%
о1
16.7%
и1
16.7%
я1
16.7%
ASCII
ValueCountFrequency (%)
1
50.0%
11
50.0%

_embedded.show.network.country.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
Russian Federation

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRussian Federation

Common Values

ValueCountFrequency (%)
Russian Federation1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:37.897675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:37.970605image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
50.0%
federation1
50.0%

Most occurring characters

ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15
83.3%
Uppercase Letter2
 
11.1%
Space Separator1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2
13.3%
i2
13.3%
a2
13.3%
n2
13.3%
e2
13.3%
u1
6.7%
d1
6.7%
r1
6.7%
t1
6.7%
o1
6.7%
Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
F1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17
94.4%
Common1
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2
11.8%
i2
11.8%
a2
11.8%
n2
11.8%
e2
11.8%
R1
5.9%
u1
5.9%
F1
5.9%
d1
5.9%
r1
5.9%
Other values (2)2
11.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

_embedded.show.network.country.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
RU

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRU

Common Values

ValueCountFrequency (%)
RU1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:38.035009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:38.107008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
100.0%

Most occurring characters

ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

_embedded.show.network.country.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
Asia/Kamchatka

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:38.170008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:38.292125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
100.0%

Most occurring characters

ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11
78.6%
Uppercase Letter2
 
14.3%
Other Punctuation1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a4
36.4%
s1
 
9.1%
i1
 
9.1%
m1
 
9.1%
c1
 
9.1%
h1
 
9.1%
t1
 
9.1%
k1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
K1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13
92.9%
Common1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a4
30.8%
A1
 
7.7%
s1
 
7.7%
i1
 
7.7%
K1
 
7.7%
m1
 
7.7%
c1
 
7.7%
h1
 
7.7%
t1
 
7.7%
k1
 
7.7%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing135
Missing (%)100.0%
Memory size1.2 KiB

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
Russian Federation

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRussian Federation

Common Values

ValueCountFrequency (%)
Russian Federation1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:38.375205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:38.450204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
50.0%
federation1
50.0%

Most occurring characters

ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15
83.3%
Uppercase Letter2
 
11.1%
Space Separator1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2
13.3%
i2
13.3%
a2
13.3%
n2
13.3%
e2
13.3%
u1
6.7%
d1
6.7%
r1
6.7%
t1
6.7%
o1
6.7%
Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
F1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17
94.4%
Common1
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2
11.8%
i2
11.8%
a2
11.8%
n2
11.8%
e2
11.8%
R1
5.9%
u1
5.9%
F1
5.9%
d1
5.9%
r1
5.9%
Other values (2)2
11.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
RU

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRU

Common Values

ValueCountFrequency (%)
RU1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:38.516414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:38.589414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
100.0%

Most occurring characters

ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing134
Missing (%)99.3%
Memory size1.2 KiB
Asia/Kamchatka

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
0.7%
(Missing)134
99.3%

Length

2022-09-04T23:45:38.672539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:45:38.765012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
100.0%

Most occurring characters

ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11
78.6%
Uppercase Letter2
 
14.3%
Other Punctuation1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a4
36.4%
s1
 
9.1%
i1
 
9.1%
m1
 
9.1%
c1
 
9.1%
h1
 
9.1%
t1
 
9.1%
k1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
K1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13
92.9%
Common1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a4
30.8%
A1
 
7.7%
s1
 
7.7%
i1
 
7.7%
K1
 
7.7%
m1
 
7.7%
c1
 
7.7%
h1
 
7.7%
t1
 
7.7%
k1
 
7.7%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Interactions

2022-09-04T23:45:28.236911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.108792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.279636image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.417818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.447043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.586383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.616867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.746368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.826165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.959334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.904878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.098757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.218275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.453911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.326216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.354634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.493375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.519035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.673384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.684877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.827299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.909000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.029342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.975919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.235363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.294356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.535977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.397216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.438309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.579376image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.598041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.751886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.761868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.901299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.994999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.099335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.053843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.354563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.377837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.617912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.466215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.518046image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.667756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.670429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.826883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.833645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.970296image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.075999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.183041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.132916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.442475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.461828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.691912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.534215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.596056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.750760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.746634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.894139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.908829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.045297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.158005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.260041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.208911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.529857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.545218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.759912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.605216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.668044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.831098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.821717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.984294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.984409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.125481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.233999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.329795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.281057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.610540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.617640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.833912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.677033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.880007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.919103image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.900192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.081167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.059409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.197481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.308216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.404795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.356211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.686472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.686640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.916138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.753033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.953939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.989029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.110723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.178168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.136724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.271685image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.386220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.478795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.433212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.760471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.763640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.999682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.832785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.027360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.065437image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.189009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.256166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.214081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.365881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.463524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.547795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.504852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.841817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.844582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:29.075678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:15.907861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.100427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.146580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.267218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.329250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.443125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.469145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.538988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.617794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.576852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.918817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.922573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:29.153668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.019749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.178557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.217580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.343215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.413505image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.513125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.558151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.743204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.686795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.647852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:26.990817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.995517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:29.292037image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.128511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.257051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.290582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.424218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.488497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.585124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.640216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.821309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.756794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.717852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.063825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.067525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:29.376074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:16.205511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:17.336886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:18.369112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:19.505385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:20.551695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:21.665274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:22.732145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:23.890336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:24.834293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:25.983360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:27.144243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:45:28.144517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-09-04T23:45:38.858009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:45:39.144578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:45:39.410184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:45:39.683260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:45:29.703937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:45:30.908333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:45:31.491554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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12121269https://www.tvmaze.com/episodes/2121269/fiksiki-4x18-sankiСанки418.0regular2020-12-252020-12-25T00:00:00+00:006.0NaNNoneNaNhttps://api.tvmaze.com/episodes/212126938199https://www.tvmaze.com/shows/38199/fiksikiФиксикиAnimationRussian[]Running6.06.02010-12-13Nonehttp://www.fixiki.ru[Friday]NaN11NaNNaNNaNNaNNaNNaNNaNNaNNone244021.0tt3886188https://static.tvmaze.com/uploads/images/medium_portrait/164/410098.jpghttps://static.tvmaze.com/uploads/images/original_untouched/164/410098.jpgNone1659704750https://api.tvmaze.com/shows/38199https://api.tvmaze.com/episodes/2370911NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/353/883109.jpghttps://static.tvmaze.com/uploads/images/original_untouched/353/883109.jpg239.0Россия 1Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaN
21984017https://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin#15 - Даня Милохин115.0regular2020-12-252020-12-25T00:00:00+00:0053.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198401748288https://www.tvmaze.com/shows/48288/roast-battle-labelcomRoast Battle LabelcomGame ShowRussian[Comedy]Running50.053.02019-12-24Nonehttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl3[Monday]NaN24NaN21.0YouTubeNaNNaNNaNhttps://www.youtube.comNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/267/668782.jpghttps://static.tvmaze.com/uploads/images/original_untouched/267/668782.jpg<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>1658030622https://api.tvmaze.com/shows/48288https://api.tvmaze.com/episodes/2362860NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31991483https://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filmeФильм о фильме1NaNinsignificant_special2020-12-2512:002020-12-25T00:00:00+00:0029.0NaNNoneNaNhttps://api.tvmaze.com/episodes/199148349280https://www.tvmaze.com/shows/49280/psihПсихScriptedRussian[Drama, Thriller]Ended62.062.02020-11-052020-12-24https://more.tv/psih[Thursday]NaN27NaN246.0more.tvRussian FederationRUAsia/KamchatkaNoneNaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/295/739859.jpghttps://static.tvmaze.com/uploads/images/original_untouched/295/739859.jpg<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>1653851744https://api.tvmaze.com/shows/49280https://api.tvmaze.com/episodes/1960733NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/410/1026277.jpghttps://static.tvmaze.com/uploads/images/original_untouched/410/1026277.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41988016https://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-5Серия 515.0regular2020-12-2512:002020-12-25T00:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198801652520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema12:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN4NaN337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNoneNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/289/723328.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/723328.jpg<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1616722619https://api.tvmaze.com/shows/52520https://api.tvmaze.com/episodes/1988016NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52062929https://www.tvmaze.com/episodes/2062929/god-of-ten-thousand-realms-1x04-episode-4Episode 414.0regular2020-12-2510:002020-12-25T02:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206292954541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese[Adventure, Anime, Fantasy]Running7.07.02020-12-21Nonehttps://v.qq.com/detail/m/mzc002007995z4v.html10:00[Monday, Friday]NaN54NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNone394467.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpghttps://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1642689319https://api.tvmaze.com/shows/54541https://api.tvmaze.com/episodes/2261133NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62353918https://www.tvmaze.com/episodes/2353918/300-year-old-class-of-2020-1x05-episode-5Episode 515.0regular2020-12-252020-12-25T03:00:00+00:0014.0NaNNoneNaNhttps://api.tvmaze.com/episodes/235391862764https://www.tvmaze.com/shows/62764/300-year-old-class-of-2020300 Year-Old Class of 2020ScriptedKorean[Comedy, Fantasy, History]EndedNaN15.02020-12-212020-12-28None[Monday]NaN44NaN30.0Naver TVCastKorea, Republic ofKRAsia/Seoulhttps://tv.naver.com/NaNNone410187.0tt14125832https://static.tvmaze.com/uploads/images/medium_portrait/414/1035476.jpghttps://static.tvmaze.com/uploads/images/original_untouched/414/1035476.jpg<p>The series is a fantasy comic web drama that tells a story of three students, who were studying in Seowon during the Joseon period accidently time travel and arrive at present-day Seowon in 2020.</p>1656357007https://api.tvmaze.com/shows/62764https://api.tvmaze.com/episodes/2353919NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72030154https://www.tvmaze.com/episodes/2030154/fox-spirit-matchmaker-9x04-episode-125Episode 12594.0regular2020-12-252020-12-25T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/203015420734https://www.tvmaze.com/shows/20734/fox-spirit-matchmakerFox Spirit MatchmakerAnimationChinese[Comedy, Anime, Fantasy, Romance]Running10.010.02015-06-26Nonehttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/[Friday]NaN68NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNone310311.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/73/183375.jpghttps://static.tvmaze.com/uploads/images/original_untouched/73/183375.jpg<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>1629636336https://api.tvmaze.com/shows/20734https://api.tvmaze.com/episodes/2153563NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82324416https://www.tvmaze.com/episodes/2324416/unique-lady-2x07-episode-7Episode 727.0regular2020-12-2512:002020-12-25T04:00:00+00:0038.0NaNNoneNaNhttps://api.tvmaze.com/episodes/232441641490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese[Drama, Comedy, Romance]Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html[Thursday, Friday, Saturday]NaN35NaN67.0iQIYINaNNaNNaNhttps://www.iq.com/NaNNone360222.0tt11939550https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpghttps://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1654382071https://api.tvmaze.com/shows/41490https://api.tvmaze.com/episodes/2324440NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92324417https://www.tvmaze.com/episodes/2324417/unique-lady-2x08-episode-8Episode 828.0regular2020-12-2512:002020-12-25T04:00:00+00:0038.0NaNNoneNaNhttps://api.tvmaze.com/episodes/232441741490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese[Drama, Comedy, Romance]Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html[Thursday, Friday, Saturday]NaN35NaN67.0iQIYINaNNaNNaNhttps://www.iq.com/NaNNone360222.0tt11939550https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpghttps://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1654382071https://api.tvmaze.com/shows/41490https://api.tvmaze.com/episodes/2324440NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

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1251972066https://www.tvmaze.com/episodes/1972066/letterkenny-9x01-american-buck-and-doeAmerican Buck and Doe91.0regular2020-12-252020-12-25T16:00:00+00:0024.0NaN<p>Post-fight with Dierks, the hicks/skids and hockey players attend an American Buck and Doe.</p>7.2https://api.tvmaze.com/episodes/197206614055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish[Comedy]RunningNaN24.02016-02-07Nonehttps://www.crave.ca/tv-shows/letterkenny[]8.295NaN109.0CraveTVCanadaCAAmerica/HalifaxNoneNaNNone302938.0tt4647692https://static.tvmaze.com/uploads/images/medium_portrait/290/726561.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726561.jpg<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1647562926https://api.tvmaze.com/shows/14055https://api.tvmaze.com/episodes/2294357NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726554.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726554.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1311972072https://www.tvmaze.com/episodes/1972072/letterkenny-9x07-ndn-nrgNDN NRG97.0regular2020-12-252020-12-25T16:00:00+00:0019.0NaN<p>Tanis starts her own energy drink.</p>8.0https://api.tvmaze.com/episodes/197207214055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish[Comedy]RunningNaN24.02016-02-07Nonehttps://www.crave.ca/tv-shows/letterkenny[]8.295NaN109.0CraveTVCanadaCAAmerica/HalifaxNoneNaNNone302938.0tt4647692https://static.tvmaze.com/uploads/images/medium_portrait/290/726561.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726561.jpg<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1647562926https://api.tvmaze.com/shows/14055https://api.tvmaze.com/episodes/2294357NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726560.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726560.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1322215237https://www.tvmaze.com/episodes/2215237/comedy-central-stand-up-featuring-7x04-rebecca-oneal-realizing-bernie-sanders-is-your-ideal-manRebecca O'Neal - Realizing Bernie Sanders Is Your Ideal Man74.0regular2020-12-252020-12-25T17:00:00+00:00NaNNaN<p>Rebecca O'Neal describes getting high and wanting to fight the coronavirus, and explains what sexting has been like during quarantine.</p>NaNhttps://api.tvmaze.com/episodes/221523740862https://www.tvmaze.com/shows/40862/comedy-central-stand-up-featuringComedy Central Stand-Up FeaturingVarietyEnglish[Comedy]RunningNaNNaN2019-01-11Nonehttp://www.cc.com/shows/comedy-central-stand-up-featuring[Friday]NaN38NaN73.0CC: StudiosUnited StatesUSAmerica/New_YorkNoneNaNNone358389.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/378/946750.jpghttps://static.tvmaze.com/uploads/images/original_untouched/378/946750.jpg<p>Get your stand-up fix from today's freshest young comedians as Comedy Central introduces you to up-and-coming comics, who are serving up quick hits of their sets.</p>1656505253https://api.tvmaze.com/shows/40862https://api.tvmaze.com/episodes/2354757NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/378/946853.jpghttps://static.tvmaze.com/uploads/images/original_untouched/378/946853.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1332341527https://www.tvmaze.com/episodes/2341527/trailer-park-boys-park-after-dark-2x31-a-very-donair-christmasA Very Donair Christmas231.0regular2020-12-252020-12-25T17:00:00+00:0030.0NaN<p>Ricky, Julian and Bubbles are full of the Christmas spirit! Find out what gifts the Boys bought each other this year, and their special treat fit for a fuckin' King. Also: One more week before 2020 fucks off!</p>NaNhttps://api.tvmaze.com/episodes/234152762418https://www.tvmaze.com/shows/62418/trailer-park-boys-park-after-darkTrailer Park Boys: Park After DarkTalk ShowEnglish[Comedy]Running30.030.02019-04-05Nonehttps://www.swearnet.com/shows/park-after-dark[Friday]NaN9NaN464.0SwearNetCanadaCAAmerica/Halifaxhttps://www.swearnet.comNaNNoneNaNtt12107408https://static.tvmaze.com/uploads/images/medium_portrait/412/1030402.jpghttps://static.tvmaze.com/uploads/images/original_untouched/412/1030402.jpg<p>Hang out with Ricky, Julian and Bubbles in Ricky's kitchen, smoking, drinking and talking about whatever the hell pops up in their fucked up brains.</p>1661520587https://api.tvmaze.com/shows/62418https://api.tvmaze.com/episodes/2380574NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1341987474https://www.tvmaze.com/episodes/1987474/205-live-2020-12-25-205-live-213205 Live #213202052.0regular2020-12-2522:002020-12-26T03:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198747422536https://www.tvmaze.com/shows/22536/205-live205 LiveSportsEnglish[]Ended60.060.02016-11-292022-02-11https://www.wwe.com/shows/wwe-205-live22:00[Friday]NaN77NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNaNNone323420.0tt6286394https://static.tvmaze.com/uploads/images/medium_portrait/96/240881.jpghttps://static.tvmaze.com/uploads/images/original_untouched/96/240881.jpg<p><i>WWE 205 Live</i>, also simply called <b>205 Live</b>, is a live professional wrestling WWE Network series produced by WWE, which exclusively features the promotion's cruiserweight division, wherein all participants are billed at a weight of 205 lbs. or less.</p><p>The final episode of the series aired on February 11, 2022. On February 18, it was replaced by <i>WWE NXT: Level Up</i>.</p>1649921818https://api.tvmaze.com/shows/22536https://api.tvmaze.com/episodes/2267545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN